BenchMARL is compatible with the TorchRL loggers.
A list of logger names can be provided in the experiment config.
Example of available options are: wandb, csv, mflow, tensorboard or any other option available in TorchRL. You can specify the loggers
in the yaml config files or in the script arguments like so:
python hydra_run.py "experiment.loggers=[wandb]"
Additionally, you can specify a create_json argument which instructs the trainer to output a .json file in the
format specified by marl-eval.
This PR introduces loggers for experiments.
Logging
BenchMARL is compatible with the TorchRL loggers. A list of logger names can be provided in the experiment config. Example of available options are:
wandb,csv,mflow,tensorboardor any other option available in TorchRL. You can specify the loggers in the yaml config files or in the script arguments like so:Additionally, you can specify a
create_jsonargument which instructs the trainer to output a.jsonfile in the format specified by marl-eval.