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Proper Way To Upload Artifacts

Proper way to upload artifacts
Good day to all. I am running a pytorch lightning notebook with ClearML integration. As was advised in lightning example just invoke task.init and all the rest will be logged. With regards to scalars and hyperparameters all fine but I have two problems:
To complete the task I used task.mark_completed()and got the following message:
<clearml.backend_api.session.callresult.CallResult at 0x7f12f7c7b6d0> 2022-05-25 16:54:57,273 - clearml.Task - WARNING - ### TASK STOPPED - USER ABORTED - STATUS CHANGED ###Whatever I do after that - I can not restart jupyter kernel - it's dead.
2. All of lightning checkpoints are stored locally and were not uploaded to the server.

Please advise what's the proper way to handle those issues.
Thank you!

Posted 2 years ago
Votes Newest


Hi GentleSwallow91 ,

  1. When using jupyter notebooks its best to do task.close() - It will bring the same affect you're interested in
  2. If you would like to upload to the server you need to add the following parameter to your Task.init() The parameter is output_uri. You can read more here - https://clear.ml/docs/latest/docs/references/sdk/task#taskinit
    You can either mark it as True or provide a path to a bucket. The simplest usage would be Task.init(..., output_uri=True)
Posted 2 years ago
1 Answer
2 years ago
one year ago