Or when running something and uploading to a s3?
Just below the filter box there is an option called Fetch/XHR
you can find the different cache folders that clearml uses in ~/clearml.conf
I would guess sosudo docker logs --follow trains-webserver
Hi @<1523701553372860416:profile|DrabOwl94> , can you check if there are some errors in the Elastic container?
Hmmmm this looks like what you're looking for:
https://clear.ml/docs/latest/docs/references/sdk/automation_controller_pipelinecontroller#stop-1
Tell me if this helps 🙂
Hi VivaciousReindeer64 , I think you can simply edit the files_server to point to the correct port 🙂
And just to make sure, you're running everything on the same machine, correct?
The server usually takes about 2-3 minutes to start up (ES takes time to warm up), does the issue still affect you?
What do you see in the agent logs? Are there any errors? Can you verify they are indeed working with the new server?
Hi @<1533619734988197888:profile|DistressedSquid12> , what errors are you getting? How are you trying to connect it?
In that case you have the "packages" parameter for both the controller and the steps
AlertCrow40 , by the way. ClearML already has an integrated tool to work on a jupyter notebook.
In a couple of lines it will open a jupyter notebook for you to work with. Further reading here: https://clear.ml/docs/latest/docs/apps/clearml_session/
🙂
Hi @<1541592241250766848:profile|BrightPenguin74> , I think this is what you're looking for
None
Hi, how did you save the dataset so far?
TartLeopard58 , I think you need to mount apiserver.conf
to the api server. This is an API configuration 🙂
Hi PunyWoodpecker71 ,
Regarding your questions:
We have an existing EKS cluster. So I'm wondering if I should deploy ClearML on the EKS cluster, or deploy on EC2 using AMI. Is there an advantage of one over the other?I think it's a matter of personal preference. Maybe SuccessfulKoala55 , can add some information.
We have a pipeline that need to run once a month to train a model. Is there an scheduler option we can config to enqueue the pipeline once a month? (It look like the Pro plan has ...
TenseOstrich47 , what do you mean exactly? Every task you run ends on 'aborted' status?
TenseOstrich47 , can you please describe what your usage is?
VexedCat68 , what errors are you getting? What exactly is not working, the webserver or apiserver? Are you trying to access the server from the machine you set it up on or remotely?
I think this might be what you're looking for:
https://clear.ml/docs/latest/docs/references/api/workers
https://clear.ml/docs/latest/docs/references/api/queues
You can access all reports through the REST API
Hi @<1544853695869489152:profile|NonchalantOx99> , how are you running the pipeline? What are the clearml
& server versions?
Do you have a snippet that reproduces this?
Can you post a minimal example here? Does this always happen or only sometimes? Also how is the pipeline run? Using autoscaler or local machines?
Hi @<1535793988726951936:profile|YummyElephant76> , did you use Task.add_requirements
?
None
How are you reporting / generating them now?
GiganticTurtle0 , which ClearML version are you using? From what I can see in the documentation to add the new parameters, you'll have to task.connect() again to add the new args
Hi @<1544853695869489152:profile|NonchalantOx99> , what actions would you exactly need to take on the machine? Genesis autoscaler allows storage on azure. If you need to add some extra commands to run before the code execution you can use the setup shell script when running inside a container
I think then this is the section you're looking for:
https://github.com/allegroai/clearml/blob/master/docs/clearml-task.md#tutorial