Alright, good to know.

No idea what's going on now, but I cannot reproduce the behaviour either.. also tried my old code posted here, but the warning doesn't pop up anymore.

I will inform once it pops again and will use the provided traceback function then.

I have a slight suspicion that it was indeed environment based on my local machine, but I have no idea what is the trigger for that.

It may or may not be related to this

2024-04-29 23:38:25,932 - clearml.Task - WARNING - Parameters must be of builtin ty...

Maybe it has something to do with my general environment? I am running on WSL2 in debian

Any help would be greatly appreciated

Alright cool!
I will check it out and let you know what it was.

If it were possible to override the checkout behaviour I would ignore all submodules anyways, but in the documentation of clearml.conf as well as the pipeline decorator I couldn't find anything that would allow me doing that.

Hey. I should have closed this..

The thing that I was looking for is called set_parameter on the task.
The HPO uses a task I created previously and I had trouble with that, since it contained a path, which wasn't available on the colab instance.
I fixed my code, so it always updates this parameter depending on the environment.

It was less of an HPO issue, more of a programming failure on the function, which didn't properly update the parameter, even though I thought it should.

If there's source URLs in the plots of the task, how can I authenticate against ClearML to properly download them?

Or is there some SDK way to download them?

I noticed that it's actually independent of the pipelines

The installed packages of the task say this:

# Python 3.11.2 (main, Mar 13 2023, 12:18:29) [GCC 12.2.0]

PyYAML == 6.0.1
clearml == 1.15.1
google google_api_core
google_cloud_storage == 2.16.0
ultralytics == 8.2.2

I do not know where the google_api_core comes from and I'd like to remove it.

Back when I wrote this, I thought HPO does something magical for overwriting the general args of the task when cloning.
Turns out it just was my code that was missing a more explicit set_parameter for this environment path.

It happens on all of my pipeline run attempts and there's nothing more that gives insight.

As an example:

python src/train.py 
ClearML Task: created new task id=102a4f25c5ac4972abd41f1d0b6b9708
ClearML results page: 

<unknown>:1: SyntaxWarning:

invalid decimal literal

<unknown>:1: SyntaxWarning:

invalid decimal literal

<unknown>:1: SyntaxWarning:

invalid decimal literal

<unknown>:1: SyntaxWarning:

invalid decimal literal

<unknown>:1: SyntaxWarning:

invalid decimal...

Sure can do

A minimal illustration of the problem:

If I run model.tune(...) from ultralytics, then it automatically will track each iteration in ClearML and each iteration will be its own task (as it should be, given that the parameters change)

But the actual tune result will not be stored in a ClearML task, since I believe there is no integration on ultralytics side to do so.

If I create a task myself which then performs model.tune(...) it will get immediately overridden by the parameters fro...

I don’t know what would cause slowness

This is the full log of the task.

I am trying to run HPO.

On another attempt with a cleaned repository (no dirty commits) I get the same result, even though it states that it got a new commit id, so I'm at a loss at what is actually going wrong here:

`Using cached repository in "/root/.clearml/vcs-cache/lvgl-ui-detector.git.7c8ae2688810ceed26c1ebcc1e911cf2/lvgl-ui-detector.git"
remote: Enumerating objects: 11, done.
remote: Counting objects: 100% (11/11), done.
remote: Compressing objects: 100% (5/5), done.
remote: Total 8 (delta 4), reused 7 ...

I cleared the vcs cache manually already, it results in the same behaviour illustrated above
(allthough the logs show that it used the cache, I had another run without cache - but don't have the logs from that)

What’s considered large in that case?

Here is the latest version with all issues ironed out.

For anyone else interested in this, I wrote a little script which pulls all the data from a given project, seems to work well enough

Here is the code doing the reporting:

def capture_design(design_folder: str):
    import subprocess, os, shutil
    from clearml import Task
    print(f"Capturing designs from {design_folder}...")
    task = Task.current_task()
    logger = task.get_logger()
    design_files = [f for f in os.listdir(design_folder) if os.path.isfile(os.path.join(design_folder, f))]
    if len(design_files) == 0:
        print(f"No design files found in {design_folder}")
        return
    widgets = {}
  ...

This here.. I know how to get the source code info, but it doesn't include the commit ID. And I also cannot access the uncommitted changes.

Thanks!

My experiments are all using YOLOv8 and they contain the data from what is gathered there automatically

Figured it out, I installed clearml[gs] but since I don't need that I removed it. it's gone now.

None

None

That is unfortunate.

I am getting the same when starting regular tasks.
I think it has something to do with my paramaters, which contain an environment variable which contains a list of datasets