python:3.7.13-bullseye

this is the case of developing AutoML: when I have a lot of datasets and the model should be nice at all datasets in average. So projects here are different versions of AutoML and I need to compare them

oh, should I use --cpu-only flag?

sorry, just found it)

@<1523701070390366208:profile|CostlyOstrich36> I need to compare aggregated values: I want to compare mean metric value of N experiments from project 1 vs mean metric value of N experiments from project 2

When I updated the URL of the remote repository in my git client

SuperiorPanda77 did you just replace “remote” for the client?

My remote in git client is ok:
ssh://git @<address>:5109<repo_path>.git
so I don’t understand why and where it changes :(

I want aggregate only final metrics from the model. For example, "Metric HO" (holdout) here:

CostlyOstrich36 I’m running the task that doesn’t need GPU by this command
clearml-task … --docker python:3.7.13-bullseye

Hi AgitatedDove14 , I’m using clearml clearml-task to queue a task in a remote agent. The git remote URL is “ ssh://git@0.0.0.0:1234/path/to/repo.git ”, clearml https://github.com/allegroai/clearml/blob/aad01056b548660bb271c4f98447b715b8ba4c7d/clearml/backend_interface/task/repo/scriptinfo.py#L909 username from it (to cover cases like https://username@github.com/username/repository.git ), so the final URL is ssh://0.0.0.0:1234/path/to/repo.git , not ssh://git@0.0.0.0:1234/path/to/repo.g...

I think docker mode is what you need to use if you want to pre-install packages in an environment

In order to use newest version I have to install the library at every run. I don’t think that building a docker image at every run is a good solution here. So the only solution is add it pythonically.

Hi CostlyOstrich36 , I can’t find any options for specifying multiple workers for one GPU. Do you mean just run this command twice?
clearml-agent daemon --queue myqueue --gpus 0

AgitatedDove14 , do you know the answer?

RoundMosquito25 hi, any updates?

when I restart the agent, it works fine, but on the second launch docker does not mount the ssh keys folder:
'-v', '/tmp/clearml_agent.ssh.rbw8o0t7:/root/.ssh',I don’t understand why. AgitatedDove14 JitteryCoyote63 could you explain the logic behind that? CLEARML_AGENT_DISABLE_SSH_MOUNT variable is not set.

So it fails with this log message:
` ...
Using cached repository in "/root/.clearml/vcs-cache/<MY_REPO>.git.893c8c47c9813c27eb1fe8d0aeb77a11/<MY_REPO>.git"
fatal: Could not read f...

AgitatedDove14

Specifically

/tmp/clearml_agent.ssh.rbw8o0t7

is the copy of the .ssh that the agent created, and now it is mounting it into the container

but why is it mounted only once? second and following containers do not mount the folder

Hi CostlyOstrich36

How are you mounting the credentials?
Is this also mounted into the docker itself?

as I wrote above, it is mounted automatically:
'-v', '/tmp/clearml_agent.ssh.kqzj9sky:/root/.ssh

What version of

ClearML-Agent

are you using?

1.3.0

so we may use more specific lib/tool or just add a if-statement for case “ssh:git@”

CostlyOstrich36 self hosted,
clearml ==1.6.4
clearml -agent==1.4.0rc0

upd: the status is changed to “Aborted”

@<1523701087100473344:profile|SuccessfulKoala55> yes, elastic is failed. don’t understand why

CostlyOstrich36 no, there is only task_id and name in response

SuccessfulKoala55 yes, I have /usr/bin/python3.8, but it doesn’t help if I set it in agent.python_binary. python3.8 set as alternative #1 for python. but conda for some reason creating env with python3.6...

Executing Conda: /home/user/conda/bin/conda env remove -p /home/jovyan/.clearml/venvs-builds/3.6 --quiet --json

ContemplativeGoat37 hi, any updates? I have a similar issue due executing clearml-data create command, also the status is stuck in “uploading”

And when I’m trying to add a file to dataset, this happens:
` Retrying (Retry(total=2, connect=2, read=5, redirect=5, status=None)) after connection broken by 'NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f20d7231430>: Failed to establish a new connection: [Errno 111] Connection refused')': /
Retrying (Retry(total=1, conn...

I've tried to run something like clearml-task ... --docker_bash_setup_script "cd $(echo /root/.clearml/venvs-builds/${PYTHON_VERSION%.*}/task_repository/...) && pip install ." but it not working because the repo is fetching after docker_bash_setup_script, so I need to run this command later

AgitatedDove14 hm, I don’t know what is the right expected behaviour, I’ve expected 2 plots. If my assumption looks right, should I make an issue on github?

sure
print(APIClient().tasks.get_all(["95db561a08304a1faac3aabcb117412e"]))
{‘id’: ‘95db561a08304a1faac3aabcb117412e’, ‘name’: ‘task’}

AgitatedDove14 the best option would be custom charts in Web UI, like in wandb: https://docs.wandb.ai/ref/app/features/custom-charts
But pdf is acceptable too.

can’t find the desired method, I thought that tasks.get_configurations is exactly what I need, but it is not

what was the old version?