AgitatedDove14

I jsut think that if I use "report_table" I might as well be able to download it as CSV or something

👍

Maybe the case is that after start / start_locally the reference to the pipeline task disappears somehow? O_O

The latest, I curl ed the docker-compose like 10 minutes ago

few minutes and I'll look at it

happens on my phone as well :man-facepalming:

Happens on my incognito aswell

Am I being punished for asking too much on 🤔

Gotcha, didn't think of an external server as Service Containers are part of Github's offering, I'll consider that

I'd be lying if I said I had time for that 🙂

CostlyOstrich36 ⬆

it will return a Config object right?

` ClearML launch - launch any codebase on remote machine running clearml-agent
Creating new task

Error: requirements.txt not found [/home/elior/Dev/Projects/XXXXX/requirements.txt] Use --requirements or --packages `

Continuing on this line of thought... Is it possible to call task.execute_remotely on a CPU only machine (data scientists' laptop for example) and make the agent that fetches this task to run it using GPU? I'm asking that because it is mentioned that it replicates the running environment on the task creator... which is exactly what I'm not trying to do 😄

Yes, I'll prepare something and send

whatttt? I looked at config_obj didn't find any set method

AgitatedDove14

So nope, this doesn't solve my case, I'll explain the full use case from the beginning.

I have a pipeline controller task, which launches 30 tasks. Semantically there are 10 applications, and I run 3 tasks for each (those 3 are sequential, so in the UI it looks like 10 lines of 3 tasks).

In one of those 3 tasks that run for every app, I save a dataframe under the name "my_dataframe".
What I want to achieve is once all tasks are over, to collect all those "my_dataframe" arti...

Committing that notebook with changes solved it, but I wonder why it failed

Do i need to copy this aws scaler task to any project I want to have auto scaling on? what does it mean to enqueue hte aws scaler?

and in the UI configuration I didn't understand where does permission management came into play

Trains docs have at no point any mention on what should I do on the AWS interface... So I'm not sure at what point I should encounter this wizard

I'm going to play with it a bit and see if I can figure out how to make it work

how do I run this wizard? is this wizard train's or aws's?

I mean I don't get how all the pieces add up

Okay, so let me get this straight

The autoscaling is basically an ever-running task (lets say on the services queue). Now, the actual auto scaling and which queues exist have nothign to do with that, and are configured in the auto scale task?

its like ps + grep together 😄

it seems that only the packages that are on the script are getting installed

` alabaster==0.7.12
appdirs==1.4.4
apturl==0.5.2
attrs==21.2.0
Babel==2.9.1
bcrypt==3.1.7
blinker==1.4
Brlapi==0.7.0
cachetools==4.0.0
certifi==2019.11.28
chardet==3.0.4
chrome-gnome-shell==0.0.0
clearml==1.0.5
click==8.0.1
cloud-sptheme==1.10.1.post20200504175005
cloudpickle==1.6.0
colorama==0.4.3
command-not-found==0.3
cryptography==2.8
cupshelpers==1.0
cycler==0.10.0
Cython==0.29.24
dbus-python==1.2.16
decorator==4.4.2
defer==1.0.6
distlib==0.3.1
distro==1.4.0
distro-info===0.23ubuntu1
doc...

I'll check the version tomorrow, about the current_task call, I tried before and after - same result

TimelyPenguin76 , this can safely be set to s3:// right?