Hi GrittyHawk31

but it could not connect to the grafana dashboard through port 3000, is there any particular reason for that? I may have missed something.

Did you run the full docker-compose.yml ?
Are you able to curl to the endpoints ?

@<1546303293918023680:profile|MiniatureRobin9>

, not the pipeline itself. And that's the last part I'm looking for.

Good point, any chance you want to PR this code snippet ?

    def add_tags(self, tags):
        # type: (Union[Sequence[str], str]) -> None
        """
        Add Tags to this pipeline. Old tags are not deleted. 
        When executing a Pipeline remotely (i.e. launching the pipeline from the UI/enqueuing it), this method has no effect.

        :param tags: A li...

Is there a quicker way to abort all running experiments in a project? I have over a thousand running anonymous data tasks in a specific project and I want to abort them before debugging them.

We are adding "select" all in the next UI version to do that as quickly as possible 🙂

This is exactly what I did here, and it is working 😞
https://demoapp.demo.clear.ml/projects/0e919ea1cc5c499b99e1ab85004b6e97/experiments/887edef09d4549e88b829a34c87d4d5b/output/execution

MortifiedDove27 did you update to the latest cleaml python package ?

Hi RobustGoldfish9 Kudos on the mount, and my apologies for forgetting to mention it.
You are absolutely right, I'll make sure we have it in the documentation, there is no way to know that obscure env variable 🙂

Not sure on the cause but if you do:

mp.set_start_method('fork', force=True)

There is no semaphore leakage

As a hack you can try DEFAULT_VERSION
(it's just a flag and should basically do Store)
EDIT: sorry that won't work 😞

Hi WickedElephant66
in the pipeline component, import the required package it should auto detect it, or in the decorator function add the argument "packages"
https://github.com/allegroai/clearml/blob/0397f2b41e41325db2a191070e01b218251bc8b2/clearml/automation/controller.py#L2941

This means that in your "Installed packages" you should see the line:
Notice that this is not a pypi artifactory (i.e. a server to add to the extra index url for pip), this is a direct pip install from a git repository, hence it should be listed in the "installed packages".
If this is the way the package was installed locally, you should have had this line in the installed packages.
The clearml agent should take care of the authentication for you (specifically here, it should do nothing).
If ...

Did you you set 'force_git_ssh_protocol: true '?
https://github.com/allegroai/clearml-agent/blob/249b51a31bee97d63f41c6d5542e657962008b68/docs/clearml.conf#L39

Is "project_name" diff for diff steps ? i.e. PipelineController(..., target_project='my_new_project') is not enough?

So I suppose clearml-agent is not responsible, because it finds a wheel for torch 1.11.0 with cu117.

The thing is, the agent used to do all the heavy parsing because pytorch never actually had a pip compatible artifactory
But now they do, so the agent basically passed the parsing to pip and just added the correct additional pytorch pip repo.
It seems we need to switch back... wdyt?

The docker crashes and I want to be abel to debug it exactly as it is run by the agent

On your machine (any machine)

pip install clearml-agent
clearml-agent build --id <taskID> --docker "local_mydocker_name"
docker run -it local_mydocker_name bash

at the end it's just another env var

It should work GIT_SSH_COMMAND is used by pip

But 

Task.create

 is used by 

Task.init

Surprisingly , no 🙂

Yep, you are right

I'm not sure the files-server supports "continue" from last position...

yes i can communicate with the server, i managed to put tasks in the queue and retrieve them as well as running tasks with metrics reporting

Through the UI or python code ?

@<1699955693882183680:profile|UpsetSeaturtle37> good progress, regrading the error, 0.15.0 is supposed to be out tomorrow, it includes a fix to that one.
BTW: can you run with --debug

Hi UnevenOstrich23

if --docker is enable that will means every new experiments will be executed into dedicated agent worker containers?

Correct

I think the missing part is how to specify the docker for the experiment?
If this is the case, in the web UI, clone your experiment (which will create a draft copy, that you can edit), then in the Execution tab, scroll down to the "base docker image" and specify the docker image to use.
Notice that you can also add flags after the docker im...

Hi @<1720249416255803392:profile|IdealMole15>
I'm assuming you mean on a remote machine with clearml-agent running ?
If you do, then you either use clearml-task to create a Task (Job) and specify the container and script. or click on "Create New Experiment" in the UI, and fill out the git repo / script and specify the docker image.
Make sense?

That said, you might have accessed the artifacts before any of them were registered

Correct 🙂

What if I register the artifact manually?

task.upload_artifact('local folder', artifact_object=' ')This one should be quite quick, it's updating the experiment

HandsomeCrow5 if you want to edit the Task object you can just use:
internal_task_representation = task.data internal_task_representation.execution.script = ... task._edit(execution=internal_task_representation.execution)This will make sure you do not need to worry about API version etc. the Task object will take care of it.
BTW: it seems a few more people wanted this ability, maybe we should edit a proper .edit method to Task. Thoughts ?

Is there any documentation on versioning for Datasets?

You mean how to select the version name ?

EnviousStarfish54 following on this issue, the root cause is that dictConfig will clean All handlers if Not passed "incremental": True
conf_logging = { "incremental": True, ... }Since you pointed that Kedro is internally calling logging.config.dictConfig(conf_logging) ,
this seems like an issue with Kedro as this call will remove All logging handlers, which seems problematic. wdyt ?

What is the link you are seeing there?

Guys, any chance you can verify the RC solves the issue?
pip install clearml==1.0.2rc0