Can you please share the endpoint link?

As of yet, I can only select ones that are visible and to select more, i'll have to click on view more, which gets extremely slow.

Can you give me an example url for the api call to stop_many?

I had the same issue before.

We want to get a clearer picture here to compare versioning with ClearML Data vs our own custom versioning

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.

I don't think so. Also I fixed it for now. Let me mention the fix. Gimme a bit

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.

My draft is View Only but the cloned toy task one is in normal Draft mode.

Basically when I have to re run the experiment with different hyperparameters, I should clone the previous experiment and change the hyperparameters then before putting it in the queue?

When I try to get local copy, I get this error.

File "load_model.py", line 8, in <module>
location = input_model.get_local_copy()
File "/home/fawad-nizamani/anaconda3/envs/ocr-sip-clearml/lib/python3.8/site-packages/clearml/model.py", line 424, in get_local_copy
return self.get_weights_package(return_path=True, raise_on_error=raise_on_error)
File "/home/fawad-nizamani/anaconda3/envs/ocr-sip-clearml/lib/python3.8/site-packages/clearml/model.py", line 318, in get_weights_package
...

Also I need to modify the code to only keep the N best checkpoints as artifacts and remove others.

can you point me to where I should look?

How do I go about uploading those registered artifacts, would I just pass artifacts[i] and the name for the artifact?

Given a situation where I want delete an uploaded artifact from both the UI and the storage, how would I go about doing that?

shouldn't checkpoints be uploaded immediately, that's the purpose of checkpointing isn't it?

I plan to append the checkpoint to a list, when the len(list) > N, I'll just pop out the one with the highest loss, and delete that file from clearml and storage. That's how I plan to work with it.

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

You can see there's no task bar on the left. basically I can't get any credentials to the server or check queues or anything.

when you connect to the server properly, you're able to see the dashboard like this with menu options on the side.

Thank you for the help with that.

I want to maybe have a variable in the simple-pipeline.py, which has the value returned by split_dataset

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

Another issue I'm having is I ran a task using clearml-task and did it using a repo. It runs fine, when I clone said task however and run it on the same queue again, it throws an error from the code. I can't seem to figure out why its happening.

Considering I don't think the function itself requires Venv to run normally but in this case it says it can't find venv

You could be right, I just had a couple of packages with this issue so I just removed the version requirement for now. Another issue that might be the case, might be that I'm on ubuntu some of the packages might've been for windows thus the different versions not existing

Thank you, I'll take a look

How would the two be different? Other than I can pass the directory to local mutable copy

So in my head, every time i publish a dataset, it should get triggered and run that task.