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 solve this issue. However it does not interpolate values

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

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".

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:

This is unfortunate as OmegaConf behaves like dict

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

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 )