Odd; switching to virtual environment results in
fatal: could not read Username for ' ': terminal prompts disabledeven though it does earlier show that:
agent.git_user = xxx

I'm trying, let's see; our infra person is away on holidays :X Thanks! Uh, which configuration exactly would you like to see? We're running using the helm charts on K8s, so I don't think I have direct access to the agent configuration/update it separately?

I'm using some old agent I fear, since our infra person decided to use chart 3.3.0 😕
I'll try with the env var too. Do you personally recommend docker over the simple AMI + virtual environment?

More complete log does not add much information -
Cloning into '/root/.clearml/venvs-builds/3.10/task_repository/xxx/xxx'... fatal: could not read Username for ' ': terminal prompts disabled fatal: clone of ' ` ' into submodule path '/root/.clearml/venvs-builds/3.10/task_repository/...

Then the username and password would be visible in the autoscaler task 😕
But it should work out of the box, as it does work like that out of the box also regardless of ClearML. The user and personal access token are used as is and it propagates down to submodules, since those are simply another git repository.
I've further checks on a different machine and it works as well 🤔

I just set the git credentials in the clearml.conf and it works out of the box

I think this is about maybe the credential.helper used

Different AMI image/installing older Python instances that don't enforce this...
For future reference though, the environment variable should be PIP_USE_PEP517=false

Ah it is.

We just inherit from logging.Handler and use that in our logging.config.dictConfig ; weird thing is that it still logs most of the tasks, just not the last one?

If that's the case, wouldn't it apply across the board? This happens in a single task within ray - the other tasks (I have many in a single run) are fine

I'll try upgrading to 1.1.5, one moment

I thought so too - so I added flush calls just in case, but nothing's changed.
This is somewhat weird since it always happens in the above scenario (Ray + ClearML), and always in the last task/job from Ray

Or do you mean the contents of the configuration, probably :face_palm: ... one moment

I'll try with 1.1.5 first, then 1.1.6rc0

e.g. a separate structured user guide with common tips, usability, best practices - https://pandas.pydata.org/pandas-docs/stable/user_guide/index.html
vs the doc, where each function is its own page, e.g.
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html

FYI @<1523701087100473344:profile|SuccessfulKoala55> (or I might be doing something wrong), but it seems the python migration code comes with carriage returns, so it fails on linux by default (one has to tr -d '\r' to use it)

EDIT: And also it defaults to /opt/allegro/data rather than the recommended /opt/clearml/data which is suggested when installing the server 🤔

It was really easy with the attached code, really 👍

I would only maybe suggest adding in the documentation, that if one uses the default recommended install location, then the script can be run without any command line arguments.
I had to momentarily look at the code to see the default paths match my own (though I could've also looked at --help default values 😛 )

Perfect now 👌 (also nice cleanup of default_new_data_root duplicate code :D)

And agent too, I hope..?

I'd be happy to join a #releases channel just for these!

Just randomly decided to check and saw there's a server 1.4 ready 🎉

/subscribe
/takemymoney

The Task.init is called at a later stage of the process, so I think this relates again to the whole setup process we've been discussing both here and in #340... I promise to try ;)

I... did not, ashamed to admit. The documentation says only boolean values.

And last but not least, for dictionary for example, it would be really cool if one could do:
my_config = task.connect_configuration(my_config, name=name) my_other_config = task.connect_configuration(my_other_config, name=other_name) my_other_config['bar'] = my_config # Creates the link automatically between the dictionaries

Running a self-hosted server indeed. It's part of a code that simply adds or uploads an artifact 🤔

https://clear.ml/docs/latest/docs/references/sdk/services_monitor

Then you can run this as a task, see also this example https://clear.ml/docs/latest/docs/guides/services/slack_alerts

That's enabled; I was aiming if there are flags to add to pip install CLI, such as --no-use-pep517

So basically I'm wondering if it's possible to add some kind of small hierarchy in the artifacts, be it sections, groupings, tabs, folders, whatever.

I think the environment variables path might work for you then?
You'd set your config with
use_credentials_chain: ${CREDENTIALS_CHAIN} Then in Python you could os.environ['CREDENTIALS_CHAIN'] = True/False before you make any calls to ClearML?

I can navigate through the projects, but selecting one task in one project, then navigating to another project and selecting a different task -> there is no suggestion to compare the tasks.

In the projects page if I show all - I just see the projects. If I search for a task of similar name, I get results, but I can't compare them via the UI.

The only way I managed so far was to create a pseudo-comparison between unrelated tasks in the same project, then remove one task from comparion, and u...

As the meme goes, well yes but actually no, since the input path is provided via argparse? I'm also not sure how this would help debug from the WebUI - you can't really see the contents of a zipped file/the configuration tab is too messy for such a nested configuration as the one we have. It's best suited as an artifact.

EDIT: Or am I missing something? Point being, when the remote execution begins, the entry point tries to run e.g. python train.py --config_file path/to/local/file.yaml ...