Yeah exact same usage.

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.

Let me give it a try.

I feel like they need to add this in the documentation 😕

apparently it keeps caliing this register_dataset.py script

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

I've been having this issue for a while now :((

I think I get what you're saying yeah. I don't know how I would give each server a different cookie name. I can see this problem being resolved by clearing cookies or manually entering /login at the end of the url

I basically had to set the tag manually in the UI

I did what you said, and got the pipeline DAG and then the executed of the step to use as ID. Thank you it worked fine.

https://clearml.slack.com/archives/CTK20V944/p1641282791308500?thread_ts=1640767505.214000&cid=CTK20V944

I actually just asked about this in another thread. Here's the link. Asking about the usage of the upload_artifact

Anyway in the resume argument, there is a default=False however const=True, what's up with that, or is const a separate parameter

My use case is that the code using pytorch saves additional info like the state dict when saving the model. I'd like to save that information as an artifact as well so that I can load it later.

I think I understand. Still I've possibly pinned down the issue to something else. I'm not sure if i'll be able to fix it on my own though.

However cloning it uses it from the clearml args, which somehow converts it to string?

I'm dumping a dict to json, how can i register that dict as an artifact

Takes in a name and an artifact object.

Doesn't matter how many times I run this code, it'll always give this same output. The tag gets appended to the list but isn't saved. Unless there's something else I'm supposed to do as well.

That's weird, it doesn't work on my main ubuntu installation but does work on a vm i created of ubuntu on windows

Ok this worked. Thank you.

Should I not run the scheduler remotely if I'm monitoring a local folder?

Also, is clearml open source and accepting contributions or is it just a limited team working on it? Sorry for an off topic question.

And casting it to bool converts it to True

There's data when I manually went there. The directory was originally hidden my bad.

Alright. Anyway I'm practicing with the pipeline. I have an agent listening to the queue. Only problem is, it fails because of requirement issues but I don't know how to pass requirements in this case.

It'll be labeled in the folder I'm watching it.

Set up is on a single machine, I have a nas mounted where I'm watching a folder, if there are sufficient images, it should publish the data but since I was using start_remotely, the code was running somewhere else and couldn't access folder.

wrong image. lemme upload the correct one.

os.listdir(location) shows nothing

I just want to be able pass output from some step as input to some other step.