If anyone knows a better way, would love to hear about it 🙂
Also the error you are showing is inside the
Is that a clear-ml lib or something custom
Might be worth running the command again with the
--verbose flag. It will likely give more details on what is causing the failure
Looks like its a
/mnt which might mean its a drive or something similar that was connected and may not be any more?
For something quick, if you create a new folder to put your dataset:
Then you can run your command with
CLEARML_CACHE_DIR='./test_dataset_location' clearml-data ... <your command here>
It will try to download into that folder
If you added a print there like:
def filter_out_pt_files(operation_type, model_info): print(model_info.__dict__) return model_info
You can see what is bring picked up. If there is a common path etc you can filter that out
If you can identify a patten in the YOLOv8 output files you can probably also filter them out 🙂
I need to add callback for it to filter out anything with
What does it look like when you instantiate the
That looks good to me, not sure
As pytorch lightning is a framework on top of Pytorch it will work the same, if not better with Clear ML
Hey 🙂 I had a similar issue today and found this solution:
In my case this codebase was using a
.pt filetype which was being picked up and logged as a model even though it was not.
import os from clearml import Task from clearml.binding.frameworks import WeightsFileHandler task = Task.init( project_name="task_project", task_name="task_name", task_type=Task.TaskTypes.training, ) def filter_out_pt_files(operation_type, model_info): is_pt_file = os.path.splitext...
One option might be to delete the local copy of the dataset and try to re-download it. Perhaps something has gone wrong with the local copy?
Hope you can get something to work 🤞
Also interested in how this is being approached 🙂 What you mentioned is exactly what I am doing