Alright, thanks for the answer! Seems legit then 🙂

in an ec2 machine

TimelyPenguin76 , no, I’ve only set the sdk.aws.s3.region = eu-central-1 param

Seems to works, I started a last one to confirm!

, causing it to unregister from the server (and thus not remain there).

Do you mean that the agent actively notifies the server that it is going down? or the server infers that the agent is down after a timeout?

extra_configurations = {'SubnetId': "<subnet-id>"}with brackets right?

I was asking to exclude this possibility from my debugging journey 😁

Yes it would be very valuable to be able to tweak that param, currently it's quite annoying because it's set to 30 mins, so when a worker is killed by the autoscaler, I have to wait 30 mins before the autoscaler spins up a new machine because the autoscaler thinks there is already enough agents available, while in reality the agent is down

Thanks SuccessfulKoala55 for the answer! One followup question:
When I specify:
agent.package_manager.pip_version: '==20.2.3'
in the trains.conf, I get:
trains_agent: ERROR: Failed parsing /home/machine1/trains.conf (ParseException): Expected end of text, found '=' (at char 326), (line:7, col:37)

Looking forward to seeing the clearml-deploy 🤩 you guys rock 🚀

ok, what is your problem then?

So this message appears when I try to ssh directly into the instance

Sure, I opened an issue https://github.com/allegroai/clearml/issues/288 unfortunately I don't have time to open a PR 🙏

I would like to try it to see if it solves some dependencies not found eventhough they are installed when using --system-site-packages

(It would be nice to have all the Pypi releases tagged in github btw)

After I started clearml-session

I sneaked a PR > https://github.com/allegroai/clearml/pull/319

But I am not sure it will connect the parameters properly, I will check now

Hi, /opt/clearml is ~40Mb, /opt/clearml/data is about ~50gb

I didn’t use ignite callbacks, for future reference:
` early_stopping_handler = EarlyStopping(...)

def log_patience(_):
clearml_logger.report_scalar("patience", "early_stopping", early_stopping_handler.counter, engine.state.epoch)

engine.add_event_handler(Events.EPOCH_COMPLETED, early_stopping_handler)
engine.add_event_handler(Events.EPOCH_COMPLETED, log_patience) `

Ha nice, good one! Thanks!

The main issue is the task_logger.report_scalar() not reporting the scalars

and I didn't have this problem before because when cu117 wheels were not available, the agent was trying to get the wheel with the closest cu version and was falling back to 1.11.0+cu115, and this one was working

Yes, I guess that's fine then - Thanks!

I guess I can have a workaround by passing the pipeline controller task id to the last step, so that the last step can download all the artifacts from the controller task.

Thanks! (Maybe could be added to the docs ?) 🙂

Indeed, I actually had the old configuration that was not JSON - I converted to json, now works 🙂

both are repos for python modules (experiment one and dependency of the experiment)

ha wait, I removed the http:// in the host and it worked 🎉

No space at the end of the diff file:
` diff --git a/configs/2.2.2_from_scratch.yaml b/configs/2.2.2_from_scratch.yaml
index 9fece48..5816f78 100644
--- a/configs/2.2.2_from_scratch.yaml
+++ b/configs/2.2.2_from_scratch.yaml
@@ -136,7 +136,7 @@ data_processing:
optimizer:
type: 'RMSprop'
args:

• lr: 2.5e-4

• lr: 1.5e-5
  momentum: 0
  weight_decay: 0 `