what do you have in the trains-agent machine in "/etc/host"

This will mount the trains-agent machine's hosts file into the docker

Is trains-agent using docker-mode or virtual-env ?

Hi SuperiorDucks36
Could you post the entire log?
(could not resolve host seems to be coming from the "git clone" call).
Are you able to manually clone the repository on the machine running trains-agent

Please attach the log 🙂

hmm I assume the reason is the cookie / storage changed?

LudicrousParrot69
I "think" I have a better handle on what you wish to do.
Is it kind of generic "serving" solution?
FYI:
Model artifact is, usually, a weights/model file. The idea that later you will be able to access it and serve it. Now the problem is (and I think this is what you are referring to) there is usually a specific piece of code tied to that model that can use it (a.k.a pyfunc)
A few ideas:
These days everyone is trying to build their models with generic interface, so that scik...

Hi LudicrousParrot69
I guess you are right this is not trivial distinction:
min: means we are looking for the the minimum value of a specific scalar. meaning 1.0, 0.5, 1.3 -> the optimizer will get these direct values and will optimize based on that
global min: means the optimizer is getting the minimum values of the specific scalar. With the same example: 1.0, 0.5, 1.3 -> the HPO optimizer gets 1.0, 0.5, 0.5
The same holds for max/global_max , make sense ?

Correct, which makes sense if you have a stochastic process and you are looking for the best model snapshot. That said I guess the default use case would be min/max (and not the global variant)

Found it, definitely a bug in the callback, it has not effect on the HPO process itself

... grab the model artifacts for each, put them into the parent HPO model as its artifacts, and then go through the archive everything.

Nice. wouldn't it make more sense to "store" a link to the "winning" experiment. So you know how to reproduce it, and the set of HP that were chosen?
No that the model is bad, but how would I know how to reproduce it, or retrain when I have more data etc..

LudicrousParrot69 I would advise the following:
Put all the experiments in a new project Filter based on the HPO tag, and sort the experiments based on the metric we are optimizing (see adding custom columns to the experiment table) And select + archive the experiments that are not usedBTW: I think someone already suggested we do the auto archiving inside the HPO process itself. Thoughts ?

Doesnt solve the issue if a HPO run is going to take a few days

The HPO Task has a table of the top performing experiments, so when you go to the "Plot" tab you get a summary of all the runs, with the Task ID of the top performing one.
No need to run through the details of the entire experiments, just look at the summary on the HPO Task.

Bugs, definitely GitHub, this is the easiest to track.
Documentation, if these are small issues, Slack is fine, otherwise, GitHub issue.
Regrading the documentation, we are working on another iteration of improvement, but if you find inaccuracies/broken links please report 🙂

Working on it as we speak 🙂 Hopefully in the next release (probably next week)

Essentially the example provide just prints out ids to the log file,

What do mean?

I see, give me a minute to check what would be the easiest

, is the team open to PRs from external people?

Yes please do! PRs are welcomed! I thought we fixed the GitHub readme to reflect it, anyhow I'll make sure we do 🙂

Hmmm:

WOOT WOOT we broke the record! Objective reached 17.071016994817196
WOOT WOOT we broke the record! Objective reached 17.14302934610711

These two seems strange, let me look into it

But the git apply failed, the error message is the "xxx already exists in working directory" (xxx is the name of the untracked file)

DefeatedOstrich93 what's the clearml-agent version?

HarebrainedBear62 this is what I have.
clearml-data will store all the files for you, and version the entire thing, make is a breeze to abstract the dataset from the code. Querying data is available using Apache Drill (though currently it is still not built into the platform, but we are planning to get there soon) Since this is Image based data/meta-data, I know the paid tier of ClearML, has n additional dedicated data management solution specifically for images, with full ability to query m...

I see, let me check something 🙂

Hi HarebrainedBear62
What's the type of data ?

They could, the problem by the time you set them,they have been read into the variables.
Maybe we should make it lazy loaded, it will also speedup the import.

others from the local environment and this causes a conflict when importing the attr module

Inside the docker ? " local environment" ?
This is all under "root" no?

ResponsiveCamel97
BTW: any reason not to allow this flexibility ?

Not really sure that's easily done ... I mean you could query the data, but I'm not sure how you would import it. Btw why would you move from pro to self hosted?

I think the ClearmlLogger is kind of deprecated ...
Basically all you need is Task.init at the beginning , the default tensorboard logger will be caught by clearml

I prepared my own image and want use this venv

No worries, it creates a "transparent" venv, it uses everything from the docker (the penalty of create a new venv is negligible 🙂 , you end up with the exact same set of packages)

Thanks LethalCentipede31 , i think (3) is the most stable solution (as it doesn't require to add another package, and should work on any python version / OS)
This is actually what we do for downloads .
DO you know if there is a minimum required python requests version ?