IrateDolphin19 ClearML provides for saving files generated as part of your code execution through the https://clear.ml/docs/latest/docs/references/sdk/task#upload_artifact . For your use case, you can have your code thus create the artifact as it runs, you can set the specific storage location when you edit your configuration, through the task's output_uri field.
Does this help?
Hi, how do you connect your configs currently?
You mean you'd like to be able to connect/create configuration objects via UI?
Ideally the json would be synced even before the task is run, but I thought integrating it to the task run would be easier
I'm not sure I understand your second request. Can you please elaborate on the exact process you're thinking of?
Clone task via UI -> Edit a config section in UI -> Enqueue it to a queue -> Worker picks it up and starts running the task -> Task is finished
What am I missing here?
I'd like the edited config object to be saved as a json file (similar to the one it was loaded from) as part of the task running (so my edits are available outside of the clearml system)
I use task.connect_configuration(json_file_path) and the json file content is loaded as a tab in the configuration view.
I'd like to be able to (after cloning the task) edit that tab, run the new task and have the task create the corresponding config file (I use this file in other parts of my workflow, outside of clearml).
