I'll have a look, at least it seems to only use from clearml import Task , so unless mlflow changed their SDK, it might still work!

https://github.com/allegroai/clearml-server/issues/134

I've also followed https://clearml.slack.com/archives/CTK20V944/p1628333126247800 but it did not help

Great, thanks!

For example, can't interact with these two tasks from this view (got here from searching in the dashboard view; they're in different projects):

I will! (once our infra guy comes back from holiday and updates the install, for some reason they setup server 1.1.1???)

Meanwhile wondering where I got a random worker from

Done https://github.com/allegroai/clearml-docs/issues/294

Using an on-perm clearml server, latest published version

TimelyPenguin76 CostlyOstrich36 It seems a lot of manual configurations is required to get the EC2 instances up and running.
Would it not make sense to update the autoscaler (and example script) so that the config.yaml that's used for the autoscaler service is implicitly copied to the EC2 services, and then any extra_clearml_conf are used/overwritten?

Thanks Alon. In the full/official documentation the clearml-data CLI is not mentioned anywhere, so perhaps it should be refreshed 😉

I think we're referring to different things here.
I won't be using the UI (and neither will my team).
But as mentioned, we've used DVC before and it adds a lot of junk metadata files to each GitHub PR (many dvc.yaml , dvc.lock and .gitignore files). We're trying to avoid that as much as possible, hence my question about GitHub pull...

AgitatedDove14 The keys are there, and there is no specifically defined user in .gitmodules :
[submodule "xxx"] path = xxx url =I believe this has to do with how ClearML sets up the git credentials perhaps?

Yes; I tried running it both outside venv and inside a venv. No idea why it uses 2.7?

AgitatedDove14 another option I thought would be nice is to actually self-sign the internal MinIO bucket, but then I get
[SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self signed certificate (_ssl.c:1076)Are you aware of any other way then (other than the secure: false flag?

Looks great, looking forward to the all the new treats 😉
Happy new year! 🎉

It's okay 🙂 I was originally hoping to delete my "initializer" task, but I'll just archive it if someone is interested in the worker data etc. Setting the queue is quite nice.

I think this should get my team excited enough 😄

This seems to be fine for now, if any future lookups finds this thread, btw
with mock.patch('clearml.datasets.dataset.Dataset.create'): ...

Yeah I managed to work around those former two, mostly by using Task.create instead of Task.init . It's actually the whole bunch of daemons running in the background that takes a long time, not the zipping.

Regarding the second - I'm not doing anything per se. I'm running in offline mode and I'm trying to create a dataset, and this is the error I get...
There is a data object it, but there is no script object attached to it (presumably again because of pytest?)

Is there a preferred way to stop the agent?

I'm working on the config object references 😉

This was changed ~14 months ago, I guess not many people use the local file storage?

https://github.com/allegroai/clearml/commit/95105cbe6a0910ee0c37db707e32549ceaf266eb#diff-9b02810ceabbfd705225d0a7181a53b956b58479e125dd64c5f6c5c8c999e142R373

Is there some default Docker image you ship with ClearML that you'd recommend, or can/should we use our own? 🙂

Yeah that works too. So one can override the queue ID but not the worker 🤔

JitteryCoyote63 please do not get used to it :D there's an open ticket/feature request to either revert this or let the user/server choose the most comfortable way

That's up and running and is perfectly fine.

I'm trying to decide if ClearML is a good use case for my team 🙂
Right now we're not looking for a complete overhaul into new tools, just some enhancements (specifically, model repository, data versioning).

We've been burnt by DVC and the likes before, so I'm trying to minimize the pain for my team before we set out to explore ClearML.

A follow up question (instead of opening a new thread), is there a way I could signal some files/directories to be copied to the execute_remotely task?

Sure! It's a bit intricate as it accommodates many of our different plotting functionalities, but this consists of the important bits (I realize we have some bad naming here, but fig[0] is actually a Figure object, and fig[1] is an Axes object):

` plt.switch_backend('agg')
sns.set_theme(...)
fig = plt.subplots(...)

sns.histplot(data, ax=fig[1], ...)
fig[1].set_xlim(...)
fig[1].set_ylim(...)
fig[1].legend(loc='best')
fig[1].set_xlabel(xlabel)
fig[1].set_ylabel(ylabel)
fig[1].set_...

I'm not sure, I'm not getting anything (this is the only thing I could fin that's weird about this project).
It has a space in the name, has no subprojects, and it just doesn't show up anywhere 🤔

@<1523701087100473344:profile|SuccessfulKoala55> could you provide some instructions?