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

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

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

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

This issue was due to a wsl proxy problem; wsl’s host name couldn't be resolved by the server and that became a problem for running agents. It works fine on Linux machines so far, however.
So no worries :D

How do I access the logs of the init process?

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

Thanks for actively replying, David
Any update on the example for saving a model from within a pipeline( specifically in .pth or h5 formats?)

So the issue is that the model url points to the file location on my machine,
Is there a way for me to pass the model url something else?

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

Hey,
So I did change the host port on the docker -compose.yml file, here's the weird error:
Why is the url being parsed with “”
I have renamed example. en v to just .env so that docker -compose can recognise the env variables(—env-file never works for me)

Thanks a lot David !

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

AgitatedDove14 Doesn't look like the same error as that thread.

Sure, in a moment

Simple doubt

http://localhost:9000 http://localhost:9000/%3Cbucket%3E
My minio instance is hosted locally at the 9000 port.

I'm good, David; hope you're good too :D
Thanks for the help! It worked :D

A simple StorageManager.download_folder(‘url’)
My minio instance is hosted locally, so I'm providing an url like ‘ http://localhost:9000/bucket-name%E2%80%99

Here's the code we're testing

This is the error that I get:

Here's what I get for the initial set up stage of clearml-serving

I'm running the clearml server on my machine, self hosted

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

I tried it - it works for a library that you can install, not for something local I suppose

Umm I suppose that won't work - this package consists of .py scripts that I use for a set of configs and Utils for my model.

Hey We figured a temporary solution - by importing the modules and reloading the contents of the artefact by pickle. It still gives us a warning, though training works now. Do send an update if you find a better solution

More context:
I have agents running the stages and the pipeline being executed locally here.