👍
Okay But we should definitely output an error on that

Thanks VexedCat68 !
This is a great example, maybe PR it to the cleamrl-servvng repo ? wdyt?

Great ascii tree 🙂
GrittyKangaroo27 assuming you are doing:
@PipelineDecorator.component(..., repo='.') def my_component(): ...The function my_component will be running in the repository root, so in thoery it could access the packages 1/2
(I'm assuming here directory "project" is the repository root)
Does that make sense ?
BTW: when you pass repo='.' to @PipelineDecorator.component it takes the current repository that exists on the local machine running the pipel...

HI BurlyRaccoon64
Yes, we did the latest clearml-agent solves the issue, please try:
'pip3 install -U --pre clearml-agent'

I think it is on the JWT token the session gets from the server
a bit of a hack but should work 🙂

session = task.session # or Task._get_default_session() 
my_user_id = session.get_decoded_token(session.token)['identity']['user']

LOL

yea the api server configuration also went away

okay that proves it

From the docs I think what's going on is that the https://opennmt.net/OpenNMT-tf/package/opennmt.Runner.html#opennmt.Runner.train is spinning a new subprocess, and the training itself happens on the subprocess.
If this is the case this will explain the lack of automagic, as the subprocess is lacking the "Task.init" call
wdyt, could that be the case ?

Sure thing 🙂

Thanks TrickyRaccoon92
I think it's about time we remove the survey link anyhow 🙂
I'll make sure it happens ..,

we need to evaluate the result across many random seeds, so each task needs to log the result independently.

Ohh that kind of makes sense to me 🙂
Yes I'm also getting:

/usr/local/lib/python3.6/multiprocessing/semaphore_tracker.py:143: UserWarning: semaphore_tracker: There appear to be 74 leaked semaphores to clean up at shutdown
  len(cache))

Not sure about that ...

should i only do mongodb

No, you should do all 3 DBs ELK , Mongo, Redis

Also what do you have in the "Configuration" section of the serving inference Task?

Hi SoreHorse95

I am exploring hiding our clearml server behind

Do you mean add additional reverse proxy to authenticate clearml-server from outside ?

Hi SarcasticSparrow10 , so yes it does, this is more efficient when using pytorch loaders, and in some other situations.
To disable it add to your clearml.conf:sdk.development.report_use_subprocess = false2. interesting error, maybe we can revert to "thread mode" if running under a daemon. (I have to admit, I'm not sure why python has this limitation, let me check it...)

It should work 🙂 as long as the versions match, if they don't the venv will install the version you need (which is great, only penalty is the install, download wise it will be cached)

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

You can definitely configure the watchdog to set the timeout to 15min, it should not have any effect on running processes, they basically ping every 30 sec alive message

Hi SubstantialElk6
Yes this is the queue the glue will pull jobs from and push into the k8s. You can create a new queue from the UI (go to the workers&queues page and to the Queue Tab and press on "create new" Ignore it 🙂 this is if you are using config maps and need TCP routing to your pods As you noted this is basically all the arguments you need to pass for (2). Ignore them for the time being This is the k8s overrides to use if launching the k8s job with kubectl (basically --override...

Hi GrievingTurkey78
Could you provide some more details on your use case, and what's expected?

I am using importlib and this is probably why everythings weird.

Yes that will explain a lot 🙂
No worries, glad to hear it worked out

I did not start with python -m, as a module. I'll try that

I do not think this is the issue.
It sounds like anything you do on your specific setup will end with the same error, which might point to a problem with the git/folder ?

(2) yes weekdays with specific hour should do exactly that:)
(3) yes I see your point, maybe we should add boolean allowing you to run immediately?
Back to (1) , let me see if I can reproduce, anything specific I need to add to the schedule call?

ReassuredTiger98 no, but I might be missing something.
How do you mean project-specific?

Hmm are you running from inside the Kaggle jupyter thing ?

Ephemeral Dataset, I like that! Is this like splitting a dataset for example, then training/testing, when done deleting. Making sure the entire pipeline is reproducible, but without storing the data long term?

RoughTiger69

Apparently,

, doesn’t populate that dict with

any keys that don’t already exist in it

.

Are you saying new entries are not added to the Dict even if they are on the Task (i.e. only entries that already exist on the dict are populated ?
But you already have all the entries defined here:
https://github.com/allegroai/clearml/blob/721569bb77d89d89e5b4f32a0ed98311c4574650/examples/services/aws-autoscaler/aws_autoscaler.py#L22

Since all this is ha...

FlutteringWorm14 an RC is out (1.7.3dc1) with the ability to configure from clearml.conf
you can now set
sdk.development.worker.report_event_flush_threshold from clearml.conf

This one should work:
` path = task.connect_configuration(path, name=name)
if task.running_locally():
my_params = read_from_path(path)
my_params = change_parmas(my_params) # change some staff

store back the change, my_params assumed to be the content of the param file (text)

task.set_configuration_object(name=name, config_taxt=my_params) `

So I'm gusseting the cli will be in the folder of python:
import sys from pathlib2 import Path (Path(sys.executable).parent / 'cli-util-here').as_posix()