what about using ENV variables? is it possible to override the config file's credentials?

so no magic "username" key? 😛

Thanks!

ok, hopefully last question on this subject 🙂
I want to use Jenkins for some pipelines. What I would like to do is have one set of credentials saved on Jenkins. Then whenever a user triggers a pipeline - this is the user that will be marked as the task's user.
If I understand the options you suggested, I'll currently need either to (1) have some mapping between users and their credentials and have all the credentials saved on Jenkins; or, (2) have each user manually add 2 environment varia...

legit, I was thinking only about task tracking, less about user based credentials. good point

cool! just to verify - I'll still need to have the credentials created in the server, right?

I was thinking about sending the parameters programatically. We have different pipelines that can generate tasks, I would like to be able to tell trains the user who started the pipeline.

yeah, maybe as an option in the Task.init

python -m http://script.as .a.module first_arg second_arg --named_arg value <- something like that

opened it, works now! Thanks.

I have access to the machine using SSH from my computer.
There doesn't seem to be any other error in the debug mode.
` Remote machine is ready
Setting up connection to remote session
Starting SSH tunnel

SSH tunneling failed, retrying in 3 seconds
Starting SSH tunnel `

nope, only port 22 is open for SSH. Is there anyway to set that as the port for clearml-session?

CLEARML_DOCKER_IMAGE=nvidia/cuda:10.1-runtime-ubuntu18.04
How do I pull the image using the agent?

Right... apparently the nvidia-docker wasn't set up. Thanks!

AgitatedDove14 is there any update on the open issue you talked about before? I think it's this one: https://github.com/allegroai/clearml/issues/214

nope, the experiment is stuck in RUNNING state

yup, it's there in draft mode so I can get the latest git commit when it's used as a base task

makes sense! thanks

Great, good to know!

And for some reason this clone is marked as completed. Not sure why, as it failed

Sure, redacted most of the params as they are sensitive:
` run_experiment {
base_task_id = "478cfdae5ed249c18818f1c50864b83c"
queue = null
parents = []
timeout = null
parameters {
# Redacted the parameters
}
executed = "d1d361d1059c4f0981200f59d7683773"
}
segment_slides {
base_task_id = "ae13cc979855482683474e9d435895bb"
queue = null
parents = ["run_experiment"]
timeout = null
parameters {
Args/param = """
[
#...

Is there an option to do this from a pipeline, from within the add_step method? Can you link a reference to cloning and editing a task programmatically? nope, it works well for the pipeline when not I don't choose to continue_pipeline

` Exception in thread Thread-5:
Traceback (most recent call last):
File "/opt/pyenv/versions/3.6.8/lib/python3.6/threading.py", line 916, in _bootstrap_inner
self.run()
File "/opt/pyenv/versions/3.6.8/lib/python3.6/threading.py", line 864, in run
self._target(*self._args, **self._kwargs)
File "/root/.clearml/venvs-builds/3.6/lib/python3.6/site-packages/clearml/automation/controller.py", line 615, in _daemon
if self._launch_node(self._nodes[name]):
File "/root/.clearml/venvs-builds/3.6/lib/pyt...

Also, tried the continue_pipeline option, didn't work as it couldn't parse the previous step that run...
ValueError: Could not parse reference '${run_experiment.models.output.-1.url}', step run_experiment could not be found

Thanks! A followup question - can I make the steps in the pipeline use the latest commit in the branch?

Hey AgitatedDove14 thanks, that works! The docker is now up and running, great success.
I have a follow up, maybe you can help debug. Now for some reason git clone doesn't work through the agent, but if I login myself to the machine and run the same command I see that fails in the log it works. The error I see is:
` cloning: git@gitlab.com:<repo_path>
fatal: Could not read from remote repository.
Please make sure you have the correct access rights
and the repository exists.

Reposito...

So apparently the NVIDIA AMI https://aws.amazon.com/marketplace/pp/prodview-e7zxdqduz4cbs
doesn't have the aws-cli installed. So I install it in the extra_vm_bash_script and now it wants a configuration. Is there any way to get that from the ENV vars you create? Do you think I should create my own AMI just for this?

Update 2: it works with the public repo using https: https://gitlab.com/gitlab-org/gitlab-foss.git but not with the private one, with
fatal: could not read Username for ' ': terminal prompts disabled

I did not, I see that there's a field for extra_trains_conf , but couldn't find clear documentation on how to use it. Is it just a reference to a trains_conf (maybe clearml_conf ?)?

No, I use an SSH connection which worked with the regular clearml-agent , we prefer to work with SSH instead of creating a git user.