sorry for the delay. ClearML capture the command line arguments but they are hydra parameters (mulitrun, config_dir, config_name, config_path, etc). I append and override some hyper parameters of the model but they are all stored as a string under "overrides".

Hi GloriousPanda26 , great, I'll check that, didn't understand if the original usage got you the configuration or not (got that with to_container you can connect_configuration )

This solve this issue. However it does not interpolate values

GloriousPanda26 doesn’t ClearML store the hydra configuration in the task?

This seems to be working:
t.connect_configuration(OmegaConf.to_container(conf, resolve=True))

Casting the configuration into a dict does not solve the problem as clearml does not capture the nested aspect of the configuration object. This is how it looks on your example:

Hi GloriousPanda26 ,

You can cast the omegaconf.dictconfig.DictConfig to a dict and connect it:

` t = Task.init(project_name="Hydra", task_name="Hydra configuration")

conf = OmegaConf.create({"a": {"b": 10}, "c": 20})
t.connect_configuration(dict(conf), name="Hydra dict configuration") `
Can this do the trick?

This is unfortunate as OmegaConf behaves like dict