Hi @<1707565838988480512:profile|MeltedLizard16>
Maybe I'm missing something but gust add to your YOLO code :

from clearml import Dataset

my_files_folder = Dataset.get("dataset_id_here").get_local_copy()

what am I missing?

how I can turn off git diff uploading?

Sure, see here
None

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

Hi @<1674588542971416576:profile|SmarmyGorilla62>
You mean on your elastic / mongo local disk storage ?

Hi WickedBee96

How can I do that?

clearml-task
https://clear.ml/docs/latest/docs/apps/clearml_task#what-is-clearml-task-for

I know this way to run it in the agent only by enqueue the draft after running it on my local machine so is there another way?

Or maybe are you looking for task.execute_remotely
https://clear.ml/docs/latest/docs/references/sdk/task#execute_remotely

Hi DilapidatedDucks58 ,
I'm not aware of anything of this nature, but I'd like to get a bit more information so we could check it.
Could you send the web-server logs ? either from the docker or the browser itself.

Please hit Ctrl-F5 refresh the entire page, see if it is till empty....

JitteryCoyote63 I think this one:
https://github.com/allegroai/clearml/blob/master/examples/services/cleanup/cleanup_service.py

delete logged images and texts though

logged images are also stored there?

FYI matplotlib imshow will create a debug image, and on complex plots the plot might get converted to image. (But shown under the plots section). All in all you might not be aware of it, but you are uploading image to your files server

Hi DilapidatedDucks58

how to force-reinstall package from github in Installed Packages

You mean make sure that the agent installs it from github?
The "Installed packages" section is equivalent to "requirements.txt" anything you can put in requirements.txt, you can put there.
For example adding to "Installed Packages"
git+Will make sure you install the latest clearml from GitHub.
Notice that you cannot have two packages with the same name (just like with regular requirements.txt)...

DilapidatedDucks58 use a full link , without the package name
git+

Notice that the new pip syntax:
packagename @ <some_link_here>Is actually interpreted by pip as :
Install "packagename" if it is not installed use the @ "<some_link_here>" to install it.

DilapidatedDucks58

is there any way to post Slack alerts for the frozen experiments?

The latest RC should solve the PyTorch data loader, do you want to test it?
pip install clearml==0.17.5rc2

DilapidatedDucks58 I'm assuming clearml-server 1.7 ?
I think both are fixed in 1.8 (due to be released wither next week, or the one after)

Hi DilapidatedDucks58 ,
Just making sure all 8 works have different worker ids? (you can see 8 in the workers page in the UI)
Also, are they running this docker or venv mode?

If that's the case check the free space in the monitoring of the experiment, you will find the free space in GB logged

Could you verify you have 8 subfolders named 'venv.X' in the cache folder ~/. trains ?

Hi SmugDog62

My guess is that there's an issue with the git repo detector.

Seems like you are correct
Can are you getting on the execution tab?
Is the repo correct?
Do you see the notebook in the uncommited changes ?

The notebook path goes through a symlink a few levels up the file system (before hitting the repo root, though)

Hmm sounds interesting, how can I reproduce it?

The notebook kernel is also not the default kernel,

What do you mean?

UptightCoyote42 nice!
BTW: make sure to clear requirements["conda"]
(not visible on the UI but tells the agent which packages were used by conda, out effort to try and see if we could do pip/conda interoperability , not sure if it actually paid off 🙂

Great to hear SourSwallow36 , contributions are always appreciated 🙂
Regrading (3), MongoDB was not build for large scale logging, elastic-search on the other hand was build and designed to log millions of reports and give you the possibility to search over them. For this reason we use each DB for what it was designed for, MongoDB to store the experiment documents (a.k.a env, meta-data etc.) and elastic-search to log the execution outputs.

Also, I would like to add some other plots t...

Hi SourSwallow36

1. The same docker image is used for all three jobs, just because it is easier to manage and faster to download. The full code is available on the trains-server GitHub. If you want to spin the containers manually, check the docker-compose.yml on the main repo, it has all the commands there
2. Fork the trains-server, commit the changes and don't forget to PR them ;)
3. Elastic search is a database, we use it to log all the experiments outputs, console logs metrics etc. This...

yes, so you can have a few options 🙂

Okay this seems correct:

pytorch=1.8.0=py3.7_cuda11.1_cudnn8.0.5_0

I can't seem to find what's the diff between the two.
Give me a second let me check if I can reproduce it somehow.

Remove this from your startup script:

#!/bin/bash 

there is no need that, it actually "markes out" the entire thing

Wait, is "SSH_AUTH_SOCK" defined on the host? it should auto mount the SSH folder as well?!

😞 anything that can be done?

So what is the difference?!

You put it there 🙂 so the assumption you know what you are looking for, or use glob? wdyt?