Then I can use ClearML-Data with it properly.

the one mentioned on the page.

I'd like to add an update to this, when I use schedule function instead of schedule task with the dataset trigger scheduler, it works as intended. It runs the desired function when triggered. Then is asleep again next time since no other trigger was fired.

Also the tutorial mentioned serving-engine-ip as a variable but I have no idea what the ip of the serving engine is.

Ok so update. It works now. last steps I did I can remember to fix it are.

In this case, it would wait until any change occurred in the project mentioned here. Even if a task started, and not a dataset change or publish or anything, it would trigger.

Okay so they run once i started a clear ml agent listening to that queue.

Also could you explain the difference between trigger.start() and trigger.start_remotely()

If it helps, I can try and record my steps in a video.

I'm assuming

Collecting idna==3.3
Using cached idna-3.3-py3-none-any.whl (61 kB)
Collecting importlib-metadata==4.8.2
Using cached importlib_metadata-4.8.2-py3-none-any.whl (17 kB)
Collecting importlib-resources==5.4.0
Using cached importlib_resources-5.4.0-py3-none-any.whl (28 kB)
ERROR: Could not find a version that satisfies the requirement jsonschema==4.2.1 (from -r /tmp/cached-reqsm1gu3664.txt (line 19)) (from versions: 0.1a0, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8.0, 1.0.0, 1.1.0, 1.2.0, 1.3.0, 2.0...

However, since a new task started in the project, it would again start a new task.

It's basically data for binary image classification, simple.

So I just published a dataset once but it keeps scheduling task.

I just copied the commands in order from the page and pasted them. All of the linux ones specifically.

I'm using clear-ml agent right now. I just upload the task inside a project. I've used arg parse as well however as of yet, I have not been able find writable hyperparameters in the UI. Is there any tutorial video you can recommend that deals with this or something? I was following https://www.youtube.com/watch?v=Y5tPfUm9Ghg&t=1100s this one on youtube but I can't seem to recreate his steps as he sifts through his code.

Alright, but is it saved as a text file or pickle file?

Honestly anything. I tried looking up on youtube but There's very little material there, especially which is up to date. It's understandable given that ClearML is still in beta. I can look at courses / docs. I just want to be pointed in the right direction as to what I should look up and study

Thanks for the help. I'll try to continue working on the vm for now.

I shared the error above. I'm simply trying to make the yolov5 by ultralytics part of my pipeline.

AgitatedDove14 Alright I think I understand, changes made in storage will be visible in the front end directly.

Will using Model.remove, completely delete from storage as well?

the storage is basically the machine the clearml server is on, not using s3 or anything

I need to both remove the artifact from the UI and the storage.

I just made a custom repo from the ultralytics yolov5 repo, where I get data and model using data id and model id.

up to date with https://fawad_nizamani@bitbucket.org/fawad_nizamani/custom_yolov5 ✅
Traceback (most recent call last):
File "train.py", line 682, in <module>
main(opt)
File "train.py", line 525, in main
assert os.path.isfile(ckpt), 'ERROR: --resume checkpoint does not exist'
AssertionError: ERROR: --resume checkpoint does not exist

Since that is an immediate concern for me as well.

when i pass the repo in clearml-task with the parameters, it runs fine and finishes. Basically when I clone and attempt the task again, I get the above assert error I don't know why.

so when I run the task using clearml-task --repo and create a task, it runs fine. It runs into the above error when I clone the task or reset it.

for which I basically forked it for myself. and made it accept clearml dataset and model ids to use.

I've basically just added dataset id and model id parameters in the args.