I'm sorry JitteryCoyote63 No 😞
I do know that the enterprise addition have these features (a.k.a vault & permissions), basically to answer these types of situations.

Hi DefeatedCrab47
You should be able to change the Web server port , but API port (8008) cannot be changed. If you can login to the web app and create a project it means everything is okay. Notice that when you configure trains ( trains-init ) the port numbers are correct 🙂

Hi SubstantialElk6
I think you are absolutely correct, it seems the glue pops all the arguments, when in fact it should maybe process them a,d convert the --env/-e
What do you think?
Aloso I assume if these are the default arguments they should actually be part of the k8s apply.yaml template no ?

Yes! I checked it should work (it checks if you have load(...) function on the preprocess class and if you do it will use it:
None

def load(local_file)
    self._model = joblib.load(local_file_name)
    self._preprocess_model = joblib.load(Model(hard_coded_model_id).get_weights())

Unfortunately that is correct. It continues as if nothing happened!

oh dear, let me make sure this is taken care of
And thank you for the reproduce code!!!

Correct.
It starts with the initial script (entry point), if it is self contained (i.e. does not interact with the rest of the repo) it will only analyze it, otherwise it will analyze the entire repo code.

ShakyJellyfish91 can you check if version 1.0.6rc2 can find the changes ?

(also could you make sure all posts regrading the same question are put in the thread of the first post to the channel?)

Hi ReassuredTiger98
I think it used to be the default and then it was removed, it has no real affect on performance but it remove all asserts ... what is your use case ? do you see any performance gains ?

Let me check what we can do 😉

Thanks!

Thanks! Let me check if we can reproduce it. BTW what's your clearml package version?

and about a month later for some reason the initial iteration seems to have changed to 0

Hmm, I see your point. Just so I fully understand, your are not saying Old experiments were changed, but new experiments (running the same code-ish) have a totally different max iterations value. Is this correct ?

Hi OddAlligator72

it 

 that they do not support PBT.

The optimization algorithm themselves are usually external (although the trivial stuff are in within Trains)
Do you have a specific PBT implementation you are considering ?

CooperativeFox72 this is indeed sad news 😞
When you have the time, please see if you can send a code snippet to reproduce the issue. I'd like to have it fixed

JitteryCoyote63 Not sure how/why the X-Pack feature was on (it is not used by the system), but you can disable it with an environment variable in the docker-compose
xpack.security.enabled=falseShould solve the problem ...

From here:
https://medium.com/@ospaarmann/tidbits-solving-the-elasticsearch-x-pack-license-issue-in-docker-d15bb22d82fd

The other way will not work, as if you start with "pip" you cannot fail ... (if you fail it's in run time which is too late)

trains-agent RC (which they tell me will be out tomorrow) will have a switch to do that, just so it is easier 🙂

Yes, it should, why?

Nice!

It seems something is wrong with the server itself...

And you cannot see it in Trains UI?

Hi PerfectChicken66

every X iterations and delete the older ones with

I have to ask, why not just overwrite the artifact? it is basically the same, no ?!

older ones with

delete_artifacts

from

Task

I think you are correct, when you delete the entire Task you can specify, delete artifacts, but it does not do that on delete_artifact 😞
You can manually do that with:
` task._delete_uri(task.artifacts["artifact"].url)
task.delete_artifact() ...

FranticCormorant35
See here https://github.com/allegroai/trains/blob/master/examples/manual_reporting.py#L42

SillyPuppy19 yes you are correct, actually I can promise you the callback will be called from a different thread (basically the monitoring thread) so it's on the user to make sure the callback can handle it .
How about we move this discussion to GitHub?

PompousBeetle71 could you try trains-agent 0.15.0rc0 ? What's the OS you are using? Are you running in docker mode, if so, what's the docker version?

I guess I got confused since the color choices in

One of the most beloved features we added 🙂

What's the host you have in the clearml.conf ?
is it something like " http://localhost:8008 " ?

BTW: you will be loosing the comments 😞

SmarmySeaurchin8 yes, the package containing the Controller is only RC, plan is to release the stable one in a couple of days. In the meantime:
pip install git+