Hooray! That works AND the feature works!
Quick follow up question, is there any way to abort a pipeline and all of the tasks it ran?

so no magic "username" key? 😛

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?

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

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.

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 `

` 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...

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

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

opened it, works now! Thanks.

yeah, maybe as an option in the Task.init

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 = """
[
#...

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.

Hey, I tried doing that but sadly it doesn't seem to work. As suggested by the ECR docs, I added:
aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin <ECR URI>To the extra_vm_bash_script in the config file. I even added a docker pull which I think worked (because it took much longer for the instances to spin up), but I still got the same error message 😞 Is there any way to debug these sessions through clearml? 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...

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

Thanks!

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

it's in the docker image, doesn't the git clone command run in the container?

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

Great, good to know!

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 ?)?

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

ok cool

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

makes sense! thanks

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