@<1523701994743664640:profile|AppetizingMouse58> Thank you very much. I forgot the volume mapping.
So can I just add the config to the async_delete container and mirror the directory structure from github?

volumes:
    - /opt/clearml/config:/opt/clearml/config
    - /opt/clearml/logs:/var/log/clearml

Hi @<1523701087100473344:profile|SuccessfulKoala55> Thank you very much.
Is there some way to verify the server uses the correct configuration files? (E.g. see it in the logs/web ui). I Just tried it does not work.
At least I can see the async_delete service complains about a missing secret, so I can start debugging there. I am using the same config as for my agents, but somehow for async_delete it does not work...

I installed my local conda environment from an environment.yml without issues, so maybe clearml makes some changes that leads to conflicts which finally leads to the cpu-version install.

Thank you! 🙂

Tried to install cudatoolkit==11.1 manually in this environemnt and got:

Found conflicts! Looking for incompatible packages.
This can take several minutes.  Press CTRL-C to abort.
failed                                                                                                                                                                         

UnsatisfiableError: The following specifications were found to be incompatible with each other:



Package xz conflicts for:
python=3....

Here it is

My driver says "CUDA Version: 11.2" (I am not even sure this is correct, since I do not remember installing code in this machine, but idk) and there is no pytorch for 11.2, so maybe it fallbacks to cpu?

Thank you very much! 😃

Just if I leave it empty, it will not work.

Thank you very much, didnt know about that 🙂

It works! Thank you very much 🙂

` =============
== PyTorch ==

NVIDIA Release 22.03 (build 33569136)
PyTorch Version 1.12.0a0+2c916ef ... Looking in indexes: ,
Requirement already satisfied: pip in /root/.clearml/venvs-builds/3.8/lib/python3.8/site-packages (22.0.4)
2022-04-07 16:40:57
Looking in indexes: ,
Requirement already satisfied: Cython in /opt/conda/lib/python3.8/site-packages (0.29.28)
Looking in indexes: ,
Requirement already satisfied: numpy==1.22.3 in /opt/conda/...

Is there a simple way to get the response of the MinIO instance? Then I can verify whether it is the MinIO instance or my client

Perfect, just what I always wanted. Looking forward to the MinIo version. Thank you:)

Very nice!
Maybe for the long-term future you could look into how to make better use of vertical space. Currently, there are 7 (5 in fullscreen mode)= different sections from content to top of the page. Maybe a compact mode would be nice or less space for content headlines.

Perfect, will do! Thank you

The one I posted 🙂
https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch

Not for the logger, I just tested it.

Now trying changing the default file server.

clearml does everything for me 😄

Is this really working for you guys? I have no clue what's wrong. Seems so unlikely that my code works with artifacts, datasets, but not logging...

AgitatedDove14 Thank you, that explains it.

Sounds good. I think it is obvious that immutability has to be managed by the user then, but this is not different from not using clearml-data, so not a disadvantage in my opinion.

Seems more like a bug or something is not properly configured on my side.

` # Connecting ClearML with the current process,

from here on everything is logged automatically

task = Task.init(project_name="examples", task_name="artifacts example")
task.set_base_docker(
"my_docker",
docker_arguments="--memory=60g --shm-size=60g -e NVIDIA_DRIVER_CAPABILITIES=all",
)

if not running_remotely():
task.execute_remotely("docker", clone=False, exit_process=True)

timer = Timer()
with timer:
# add and upload Numpy Object (stored as .npz file)
task.upload_a...

Or I am using this method wrong.

I think in the paid version there is this configuration vault, so that the user can pass their own credentials securely to the agent.

@<1576381444509405184:profile|ManiacalLizard2> Just so I understand correctly:
You are saying that in your local, user-specific, clearml.conf you set the api.files_server , but in your remote, clearml-agent, clearml.conf you left it empty?

@<1576381444509405184:profile|ManiacalLizard2> Yes, exactly. I just didn't know how, but now it is all working 🙂
And yes, I have multiple credentials in the clearml.conf of the agents. It's not a good solution, but since I am currently limited to the free version of ClearML, it is the best I could do.

Thanks a lot, now I think I understand.

Debug samples can only be controlled via api.file_server (or programatically)

Could you guide me how to approach this programmatically? Can I implement my own storage adapter for debug samples with ClearML interfaces or am I on my own?