Yep, no clue why I had two of them either;
It started my pipeline and a few seconds in, another pipeline shows up

So I'm trying to run my pipeline file that runs a pipeline locally and logs metrics and stuff to the clearml server

What is the detached flag for?

Here's the code we're testing

I replaced local host with the host name of the server in the credentials

More context:
I'm using agents to remotely execute the pipeline,
A weird observation is that adding ‘import timm’ to the pipeline controller doesn't make the agent running the pipeline controller install timm.
Adding to this,
Here I want to run the entire pipeline remotely - both the controller and the components run on agents

version: "3.6"
services:

apiserver:
command:
apiserver
container_name: clearml-apiserver
image: allegroai/clearml:latest
restart: unless-stopped
volumes:
/opt/clearml/logs:/var/log/clearml
/opt/clearml/config:/opt/clearml/config
/opt/clearml/data/fileserver:/mnt/fileserver
depends_on:
redis
mongo
elasticsearch
fileserver
environment:
CLEARML_ELASTIC_SERVICE_HOST: elasticsearch
CLEARML_ELASTIC_SERVICE_PORT: 920...

So, I replaced line 65 in your docker-compose file with image: elasticsearch:7.16.2 so that it pulls the image from the dockerhub registry than the registry at http://docker.elastic.co , I just want to confirm if this is okay with the functioning of clearml

Super sorry for being a bit late!

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

That's alright?

Removing the “” in my env file gives me a timeout issue

I'm facing the issue during the initial set up of clearml serving - i.e the step where you use docker-compose to launch the serving containers

Yep, that's exactly what's happening.
However here's what I want to do:
upload model to clearml’s fileserver and get the model url in the details for easy download

Oh

Alright then, the server worked as it should so far, thanks 😄

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

Also, does PipelineDecorator.upload_model store anything on the fileserver ? I can't seem to understand the use of PipelineDecorator.upload_model() apart from making a model appear on the pipeline task

Do let me know about the cpu cores

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

Exactly what I thought;
That's so odd

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

Not local .py files

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

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

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

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