Any updates on trigger and schedule docs 🙂

this task - https://github.com/allegroai/clearml/blob/5a9155b2039413280f13dfded1121470c4c4323d/examples/pipeline/step2_data_processing.py

What’s the point of saying General?

create_task_from_functionI was looking at options to implement this just today, as part of the same remote debugging that I was talking of in this thread

On a related note - is it possible to get things like ${stage_data.artifacts.dataset.url} from within a task rather than passing params in add_step ?

Yeah mostly. With k8s glue going, want to finally look at clearml-session and how people are using it.

From code perspective what changes?

So General would have created a General instead of Args?

I am doing something like this with a yaml based pipelines DSL

Example:

name: ml-project template: nbdev pipelines_runner: gitlab pipelines: pipeline-1: steps: - name: "publish-datasets" task_script: "mlproject/publish_datasets.py" - name: "training" task_script: "mlproject/training.py" parents: ["publish-datasets"] - name: "test" task_script: "mlproject/test.py" parents: ["training"]Have cli which goes through each of the tasks and creates them

AS in clone the task from the UI and run it

Hey SuccessfulKoala55 - this was related to the previous message. Had it clarified with AgitatedDove14

is it known?

Any reason to not have those as two datasets?

Updating to 1.1.0 gives this error:

ERROR: Could not push back task [e55e0f0ea228407a921e004f0d8f7901] to k8s pending queue [c288c73b8c434a6c8c55ebb709684b28], error: Invalid task status (Task already in requested status): current_status=queued, new_status=queued

I guess the question is - I want to use services queue for running services, and I want to do it on k8s

AgitatedDove14 - thoughts on this? I remember that it was Draft before, but maybe because it was in a notebook vs now I am running a script?

Or in the code? - https://github.com/allegroai/clearml/blob/master/clearml/task.py

What happens if I do blah/dataset_url ?

AgitatedDove14 - these instructions are out of date? https://allegro.ai/clearml/docs/docs/deploying_clearml/clearml_server_kubernetes_helm.html

It did pick it from the task?

The repo seems to be

If i publish a keras_mnist model and experiment on, each of it gets pushed as a separate Model entity right? But there’s only one unique model with multiple different version of it

Do people generally update the same model “entry”? That feels so wrong to me…how do you reproduce a older model version or do a rollback etc?

I have a wrapper SDK over clearml that includes default conf and others are loaded from secret manager / env vars as needed

Thanks AlertBlackbird30

AgitatedDove14 - any doc yet for scheduler? Is it essentially for just time based scheduling?

I then install this wrapper SDK in my containers, notebook instances etc

Ok couldn’t see it in the docs - https://clear.ml/docs/latest/docs/references/sdk/task

sure, will do AlertBlackbird30

🙏