Tried all three solutions right now;
Oddly enough it doesn't work :(

I had initially just pasted the new credentials in place of the existing ones in my conf file;
Running clearml-init now fails at verifying credentials

That's alright?

What exact ly does the error mean

SuccessfulKoala55 Any leads f or the above error i n running the script?

Exactly what I thought;
That's so odd

We're initialising a task to ensure it appears on the experiments page;
Also not doing so gave us issues of ‘Missing parent pipeline task’ for a set of experiments we had done earlier

This is the error that I get:

Though as per your docs the add_requirements is for a requirements .txt

Also, does clearml by default upload models if we save them using torch.save?

So I did exactly that, and the name and path of the model on the local repo is noted;
However, I want to upload it to the fileserver

How would you structure PyTorch pipelines in clearml? Especially dealing with image data

How do I access the logs of the init process?

But it seems to upload the model on noticing torch.save irrespective

Configuration completed now; I t was a proxy issue from my end
However running my pipeline from a different m achine still gives me a problem

I have hidden the host name as well

Hey David , I was able to get things uploaded to the fileserver by a change in the conf

Yes they have been set up as per the new credentials created on the server

Is there a way to store the return values after each pipeline stage in a format other than pickle?

Also, if I were to move to g pu machines, how do I assign more cores to a worker or so?

Thanks a lot David!

I'm asking this because my kwargs is observed as an empty dict if printed

Nop e

Here's the code we're testing

How do I provide a specific output path to store the model? (Say I want to server to store it in ~/models)
I'm training my model via a remote agent.
Thanks to your suggestion I could log the model as an artefact(using PipelineDecorator.upload_model()) - but only the path is reflected; I can't seem to download the model from the server

Also,
How do I just submit a pipeline to the server to be executed by an agent?
Currently I am able to use P ipeline Decorator.run_locally() to run it ;
However I just want to push it to a queue and make the agent do it's trick, any recommendations ?

Yep, the pipeline finishes but the status is still at running . Do we need to close a logger that we use for scalers or anything?

Not local .py files