You can save it as a dataset and then fetch it during run time, or am i missing something?
I assumed I would need to upload it and then reference it somehow?
ClearML downloads/caches datasets to ~/.clearml/
folder so yes, you need to modify your code.dataset_folder = Dataset.get(project_name=, dataset_name=, version=).get_local_copy() file_json_path = os.path.join(dataset_folder, 'file.json')
Is not direcly cached in the ~/.clearml
folder. There are some directories inside (one for storage, one for pip, another for venvs, etc.
So in your case it would be stored in ~/.clearml/cache/storage_manager/datasets/ds_{ds_id}/my_file.json
I wouldn't be able to pass in ~/.clearml/cache/storage_manager/datasets/ds_{ds_id}/my_file.json
as an argument?
so it caches to ~/.clearml/ any files that are under the same project name?
you would, but I’d advise against it, since that is not the intended way
Sure. My git repo myProject.git
does not have file.json
checked into VCS. I'd like to add this file at experiment runtime or equivalent.
do I have to fetch it via code? I was hoping to not modify my scripts
After proving we can run our training, I would then advise we update our code base
Could I simply just reference the files by name and pass in a string such as ~/.clearml/my_file.json
This would be a short term solution as we build a proof of concept
I’m afaid I don’t think there is a way to go around this without modifying your code.
ok, but if you were to run it from a different machine (or a different user!) it wouldn’t work