it’s not implemented right,

I think we forgot to add it as an argument (the query models supports it, but it is not passed to the call)

RobustRat47
What exactly is the error you are getting ? (I remember only the latest Triton solved some issue there)

JitteryCoyote63 no I think this is all controlled from the python side.
Let me check something

Just to make sure I understand, running locally creates the Args/command correctly, then when actually executed on the remote machine (i.e. execute_remotely creates the correct Args/command But when the agent actually executes it) it updates back the Args/command as a list. Is that a correct description ?

@<1523704157695905792:profile|VivaciousBadger56> regrading: None
Is this a discussion or PR ?
(general ranting is saved for our slack channel 🙂 )

Hi IrritableGiraffe81
Can you share a code snippet ?
Generally I would try
task = Task.init(..., auto_connect_frameworks={"pytorch': False, 'tensorflow': False)

So I had to add it explicitly via a docker init script

Oh yes, that makes sense, can't think of a better hack other than sys.path.append(os.path.join(os.path.dirname(__file__), "src"))

I still can't get it to work... I couldn't figure out how can I change the clearml version in the runtime of the Cleanup Service as I'm not in control of the agent that executes it

Let's take a step back. Let's remove the clearml-services from the docker compose for a second, and run it manually (then you can control everything). Once you have it running manually, let's try to replicate the setup back to the docker compose, make sense ?

DeliciousBluewhale87 you can try:
` import sqlite3
import pandas as pd

conn = sqlite3.connect('test_database')

sql_query = pd.read_sql_query ('''
SELECT
*
FROM products
''', conn)

sql_query.to_csv(...) `

Seems like it is working (including seaborn)

OK - the issue was the firewall rules that we had.

Nice!

But now there is an issue with the

Setting up connection to remote session

OutrageousSheep60 this is just a warning, basically saying we are using the default signed SSH server key (has nothing to do with the random password, just the identifying key being used for the remote ssh session)
Bottom line, I think you have everything working 🙂

Wait IrritableOwl63 this looks like ti worked, am I right ? huggingface was correctly installed

Hi CynicalBee90
Sorry, I missed the reply.

"I think we’ll leave the checkmark and the warning and just write SSPL below," Sounds like a good solution 👍
2. I have to admit, I would just write "language agnostic", but I will not insist further, so if you feel "platform" helps in explaining the reasoning, I'm with you.
3. "... to do smart analysis on my logged data easily, ..."
If this is the criteria, none of the options is Very easy, but they all have an interface.. not sure how to com...

Hi @<1547028074090991616:profile|ShaggySwan64>

I'm guessing just copying the data folder with rsync is not the most robust way to do that since there can be writes into mongodb etc.

Yep

Does anyone have experience with something like that?

basically you should just backup the 3 DBs (mongo, redis, elastic) each one based on their own backup workflows. Then just rsync the files server & configuration.

have a CI/CD (e.g Github Actions) thats update my “production” pipeline on ClearML UI,

I think this is the easiest way, basically the CI/CD launches a pipeline (which under the hood is another type of Task), by querying the latest "Published" pipeline that is also Not archived, then cloning+pushing it to execution queue.
In the UI when you want to "upgrade" the production pipeline you just right click "Publish" on the pipeline you want to launch. Another way is to do the same with Tags...

The only workaround I can think of is :
series = series + 'IoU>X'
It doesn't look that bad 🙂

It is http btw, i don't know why it logged https://

This is odd could it be it automatically forwards to https ?
I would try the certificate check thing first

size 0

Many thanks!

Hi SweetGiraffe8
could you try with the latest RC
pip install 0.17.5rc2

yea, does the enterprise version have more functionality like this?

yes, all sorts of bit and pieces for easier DevOps / K8s etc.

JitteryCoyote63 not yet 😞
I actually wonder how poplar https://github.com/pallets/click is ?

but not as a component (using the decorator)

Hmm yes, I think that component calling component as an external component is not supported yet
(basically the difference is , is it actually running as a function, or running on a different machine as another pipeline component)

I noticed that when a pipeline step returns an instance of a class, it tries to pickle.

Yes this is how the serialization works, when we pass data from one node to another (by design it supports multiple mach...

Does that work?

BroadSeaturtle49 btw: RC with a fix should be out after the weekend

Hi RoundSeahorse20
Try the following , let me know if it worked.
clear_logger = logging.getLogger('clearml.metrics') clear_logger.setLevel(logging.ERROR)

Hi @<1547028031053238272:profile|MassiveGoldfish6>
What is the use case? the gist is you want each component to be running on a different machine. and you want to have clearml do the routing of data and logic between.
How would that work in your use case?

Hi @<1535069219354316800:profile|PerplexedRaccoon19>
What do you mean by simulate?
You can manually setup and run a Task if you need,
'clearml-agent execute --id task_id' add --docker for docker mode.
This will setup the env and run the task

I found "scheduler" on allegroai github, is it something related to the case I want to make?

MoodyCentipede68 it is exactly what you are looking for 🙂
Do notice that you need to make sure you have your services queue configured and running for that to work 🙂

This is the prerequisites of the docker service installed on the host machine (where the agent is running)
Basically follow: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html
https://docs.docker.com/compose/gpu-support/