Sure, I can polish my code of corse, but wanted to first check if there is to be any useful.

and in the future I do want to have an Agent on the k8s cluster, but then this should not be a problem I guess as the user is set during Task.init , right?

I can't make anything appear in the console part of the ui

I could have been more inventive as well 😄

We have a training template that is a k8s job definition (yaml) that creates env variables inside the docker images that is used for tranining, and those env variables are credentials for ClearML. Since they are taken from k8s secrets, they are the same for every user.

I can create secrets for every new user and set env variables accordingly, but perhaps you see a better way out?

traceback:
` Traceback (most recent call last):
File "/home/marek/nomagic/monomagic/ml/tiresias/calibrate_and_test.py", line 57, in <module>
Task.add_requirements('requirements.txt')
File "/home/marek/.virtualenvs/tiresias-3.9/lib/python3.9/site-packages/clearml/backend_interface/task/task.py", line 1976, in add_requirements
for req in pkg_resources.parse_requirements(requirements_txt):
File "/home/marek/.virtualenvs/tiresias-3.9/lib/python3.9/site-packages/pkg_resources/_init...

thanks! is this documented? (I am wondering whether I could have avoided bothering you with my question in the first place)

task.data.user is the user id, can I get it in the text form?

I don't see such a method in the docs, but it seems so natural that decided to ask.

I am only getting one user for some reason, even though 4 are in the system

SuccessfulKoala55 that worked, thanks a lot!

where is the endpoint located? I can't find it, were only able to find this:
https://github.com/allegroai/clearml/blob/ccc8e83c58336928424ed14b176306b149258512/examples/services/monitoring/slack_alerts.py#L55

pro plan

👍

great, thanks!

thanks!

but it is a guess

I think there was some problem how shutil.copytree works in python3.6 with broken links

there is a broken symlink in the original repository

@<1523701435869433856:profile|SmugDolphin23> None

@<1523701435869433856:profile|SmugDolphin23> let me know if you need any help in reproducing

The problem started appearing when I started to use joblib with a simple memory caching mechanism.

@<1523701087100473344:profile|SuccessfulKoala55> I have the same problem with diskcache

I am seeing such warnings clearml.model - WARNING - 9 model found when searching

@<1523701435869433856:profile|SmugDolphin23> will send later today

@<1523701435869433856:profile|SmugDolphin23> it took some time, but I was able to cut 90% of the code, just dataloading remains and the problem persists (which is fortunate, as it makes it easy to replicate). Please have a look.

@<1523701435869433856:profile|SmugDolphin23> it did not help, shall I create smallest example when it does not work and paste it here?

@<1523701087100473344:profile|SuccessfulKoala55> any ideas what can be the cause?

@<1523701087100473344:profile|SuccessfulKoala55> FYI

@<1523701087100473344:profile|SuccessfulKoala55> I am using it as follows:

after calling clearml.Task.init() I create an object:

cache = Cache('/scidata/marek/diskcache')

and then in the loading function I do:

   if cache_arg in load_and_crop.cache:                                                                                                                                                                     
         return load_and_crop.cache[cache_arg]            ...