Yeah that could be one approach.

I mean, is it possible to create a trigger task that reads a message from a queue? And that message contains information about whether a pipeline needs to be triggered or not

Thanks maestro. Will give this a go

Another update - the tasks run fine and installs the packages from the correct index URL. However, by default, py_db @ git .. is added in the installed packages panel. Could this be from a requirements.txt file somewhere? To get it to work, I have to remove the @ git part, and then it works. Just very strange that it defaults to git pip install 🤔

0.17.5rc5

matplotlib == 3.1.3

Haha no not that much, I was just trying to play around with removing tasks etc, and didn't want to remove tasks created by co-workers.

Out of interest, is there a reason these are read-only? The code for these tasks is on github right?

Here is the error message from the console
Collecting git+ssh://****@github.com/15gifts/py-db.git Cloning ssh://****@github.com/15gifts/py-db.git to /tmp/pip-req-build-xai2xts_ Running command git clone -q 'ssh://****@github.com/15gifts/py-db.git' /tmp/pip-req-build-xai2xts_ ERROR: Repository not found. fatal: Could not read from remote repository. Please make sure you have the correct access rights and the repository exists.

Reason I am asking is because we have servers with large RAM capacity, but minimal storage capacity, meaning that objects held in memory can sometimes surpass storage capacity if export is required

While we are here - excuse my ignorance for now if this has already been stated in the docs ..

Is it possible to launch multiple clearml-agents on a dedicated clearml-agent server? I noticed that with one agent, only one task gets executed at one time

It should be a draft, so that it can be enqueued

Ideally, I want to avoid re-inventing the wheel so if this functionality already exists with some examples then it would be great if someone could point me to it

yes it does, but that requires me to manually create a new agent every time I want to run a different env no?

great, thanks! will give that a go

How we resolved this issue is by developing a package to deal with the connecting and querying to databases. This package is then used inside the task for pulling the data from the data warehouse. There is a devops component here for authorising access to the relevant secret (we used SecretsManager on AWS). The clearml-agent instances are launched with role permissions which allow access to the relevant secrets. Hope that is helpful to you

I removed it and I still get the same error 😞

Hey Alon. Thanks for the response. I'm not quite sure I follow your answer. Where do I add this git+ssh and how?

In particular, what does the external trigger poll? Is it a queue somewhere on clearml, or any arbitrary queue like SQS is supported?

Never mind. I think I figured it out. Thanks for your help 🙂

I don't think we explicitly pass the package path to the agent. I expect it to run a regular pip install but it seems to be doing it via git somehow

its a seaborn heatmap that needs to be plotted. not sure if that is useful at all

This is a suspicion only. It could be something else. In my case, there is no artifact or other config with a dict containing that key. Only the label map contains that key

Oh, that may work. Is there any docs/demos on this?

Any news on this bug?

In particular, I am trying to find a neat way to query all models available, and use tags to know the context. As it stands, I log the model accuracies/RMEs as part of the metadata, alongside the training data filepath. Issue is that this is not the neatest way of querying models across tasks without a lot of laborious manual lifting. Suggestions welcome

Thanks Ariel, will give it a watch now

Sounds good to me. Thanks Martin 🙂

Just upgraded matplotlib, going to test now

Nope, from a remote server. It was that I had installed the package from git locally, so when pushing the task, clearml assumed it should also install from git. I since installed the package from the private pypi and it all works as expected now 🙂

No rush, thanks for looking into it and sorry for tagging everyone here 😂

I don't even know if I have a valid concern for this. Just a little worried as airflow is accessible by more departments than just DS, which could result in some disasters