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

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 :(

CostlyOstrich36 no, there is only task_id and name in response

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.

AgitatedDove14 , do you know the answer?

AgitatedDove14

Are you saying the second time this line is missing?

Yes.

Can you send the full Task log?

I will send the log in direct messages.

I’ve found the answer:
https://github.com/allegroai/clearml-agent/issues/42#issuecomment-887331420

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

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 no, it’s not a request.

I have custom python class, that uses a lot of models from frameworks that supported by ClearML already. I want to enable auto reporting for all models by using command clearml_task.connect(my_custom_class_instance) , but it doesn’t work the way I need it to — there is the only one loss curve, because because this graph is redrawn every time a new instance starts training.
Is there any way to reporting all instances inside my custom class without ...

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

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

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

AgitatedDove14 sorry, no, in fact my configuration looks like:

` ...

agent.git_user=""
agent.git_pass=""
agent.git_host=""

agent.package_manager.extra_index_url= [

]

agent {
worker_id: ""
worker_name: ""
force_git_ssh_protocol: true

... `

sorry, just found it)

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

AgitatedDove14 done) btw, could you show me the place in the code where scalars are written? I want to make a hotfix

CostlyOstrich36 thank you! appreciate the quick response!

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

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

@<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

python:3.7.13-bullseye

@<1523701181375844352:profile|ExasperatedCrocodile76> hi, try to pass “--network=host” to --docker_args
example:

clearml-task --project project --name name --script run.py --queue queue --requirements requirements.txt --docker python:3.7.13-bullseye --docker_args "--cpus=8 --memory=16g --network=host"

CostlyOstrich36 it is ok if I use agent in docker mode, but what should I use in other cases?

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

ConvolutedFox44 any updates?

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

ContemplativeGoat37 and new