Hi DefeatedCrab47 ,

You can set the HP with a dict, like:

Task.current_task().set_user_properties( { "property_name": {"description": "This is a user property", "value": "property value"}, "another_property_name": {"description": "This is another user property", "value": "another value"}, "yet_another_property_name": "some value" } )or list of dicts, like:

Task.current_task().set_user_properties( [ { "name": "property_name", "description": "This is a user property", "value": "property value" }, { "name": "another_property_name", "description": "This is another user property", "value": "another value" } ] )
can one of those do the trick for you?

DefeatedCrab47 If I remember correctly v1+ has their arguments coming from argparse .
Are you using this feature ? 2. How do you set the TB HParam ? Currently Trains does not support TB HParams, the reason is the set of HParams needs to match a single experiment. Is that your case?

You can send "yet_another_property_name": 1 too, or you can do
"another_property_name": {"description": "This is another user property", "value": "1", "type": "int"}

As there are quite some hparams, which also change depending on the experiment, I was hoping there was some automatic way of doing it?

For example that it will try to find all dict entries that match "yet_another_property_name": "some value" , and ignore those that don't.
The value has to be converted to a string btw?

DefeatedCrab47 can you share model.hparams format?