it fails but with COMPLETED status

Which Task is marked "completed" the pipeline Task or the Step ?

The easiest would be as an artifact (I think).
Let's assume you put it into a csv file (with pandas or mnaually)
To upload (from the pipeline Task itself):
task.upload_artifacts(name='summary', artifact_object='~/my/summary.csv')Then if you want to grab it from anywhere else:
task = Task.get_task(task_id='HPO controller Task id here') my_csv = Task.artifacts['summary'].get_local_copy()
If you want to store as dict it might be even easier:
` task.upload_artifacts(name='summary', artifa...

Verified, you are correct "." in label enumeration will break the clone .
I'll make sure this bug is passed to backend guys to fix. Thanks TenseOstrich47 !
meanwhile maybe "_" instead ? 😁

Well it should work out if the box as long as you have the full route, i.e. Section/param

Hi @<1541592204353474560:profile|GhastlySeaurchin98>

During our first large hyperpameter run, we have noticed that there are some tasks that get aborted with the following console log:

This looks like the HPO algorithm doing early stopping, which algo are you using ?

that embed seems to be slightly off with regards to where the link is actually pointing to

I think this is the Slack preview... 😞

yes exactly my thinking 👍

Optional[Sequence[Union[str, Dataset]]]None, list of string or list of Datasets objects
(each one is a parent (supporting multiple parents)

Hi JealousParrot68
This is the same as:
https://clearml.slack.com/archives/CTK20V944/p1627819701055200
and,
https://github.com/allegroai/clearml/issues/411

There is something odd happening in the files-server as it replaces the header (i.e. guessing the content o fthe stream) and this breaks the download (what happens is the clients automatically ungzip the csv).
We are working on a hit fix to he issue (BTW: if you are using object-storage / shared folders, this will not happen)

Sounds good 🙂

Hi EnviousStarfish54
Verified with the frontend / backend guys.
Backend allows to search for "all" tags, and frontend will add a toggle button for the UI to select or/all for the selected Tags.
Should be part of the next release

ElegantCoyote26 I don't think Keras logs it anywhere unless you have TB, so nowhere to take the data from...
In short, yes you have to have TB :)

Hi ElegantCoyote26
What's the docker / docker-compose version?
What's the OS?

hi @<1727497172041076736:profile|TightSheep99>
yes, but also set the dataset chunk filesize to something smaller than the default 500Gb (--chunk-size)
None

Since this fix is all about synchronizing different processes, we wanted to be extra careful with the release. That said I think that what we have now should be quite stable. Plan is to have the RC available right after the weekend.

Could you see if that makes a difference ?

BTW:

======> WARNING! Git diff to large to store (1327kb), skipping uncommitted changes <======

This means all your git changes are stored as an artifact, which is consistent with the "wait for upload" message.

ETA for the next release is end of the month/early March, it is planned to include many other improvements 🙂

Hi FunnyTurkey96
Any chance you can try to run with the latest form GitHub (i just tested your code and it seemed to work on my machine).
pip install git+

Thank you!

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

you need to set

CLEARML_DEFAULT_BASE_SERVE_URL: 

So it knows how to access itself

Nice!!!!!

Hmm that is odd.
Can you verify with the latest from GitHub?
Is this reproducible with the pipeline example code?

FYI: if you need to query stuff you can always look directly in the RestAPI:
https://github.com/allegroai/clearml/blob/master/clearml/backend_api/services/v2_9/projects.py
https://allegro.ai/clearml/docs/rst/references/clearml_api_ref/index.html

Just to clarify, where do I run the second command?

Anywhere just open a python console and import the offline task:
from trains import TaskTask.import_offline_session('./my_task_aaa.zip')

Related, how to I specify in my code the cache_dir where the zip is saved?

This is the Trains cache folder, you can set it in the trains.conf file:
https://github.com/allegroai/trains/blob/10ec4d56fb4a1f933128b35d68c727189310aae8/docs/trains.conf#L24

Hi @<1624941407783358464:profile|GrievingTiger47>
I think you should try to contact the sales guys here: None

Alright I have a followup question then: I used the param --user-folder “~/projects/my-project”, but any change I do is not reflected in this folder. I guess I am in the docker space, but this folder is not linked to my the folder on the machine. Is it possible to do so?

Yes you must make sure the docker can mount a persistent folder for you to work on.
Let me check what's the easiest way to do that

How do I tell from the ClearML UI which datasets version am I using?

Hi SubstantialElk6 , what exactly do you mean by "ClearML UI which datasets am I using" ? Do you mean is there an auto magic adding the dataset ID when you call Data.get() in your code ? (because if you are I specifically remember discussing adding this feature a few days ago, which you just bumped the priority of 😉 )

UnevenOstrich23

but interesting that auto-reload config does not working as I expected.

Unfortunately the trains-agent does not support auto reloading the config file yet. If you think this will be a great feature, please feel free to open a GitHub feature request issue 🙂