The main script can be found in execute_unlearning_algorithms.py.
It takes as an input the following parameters:
- model
- weight_path
- dataset
- dataset_path is already downloaded
- classes --> number of classes in this dataset
- target_class --> target forget class id
- gan_output --> use gan output vs original dataset
- gan_dataset_size
- learning_rate
- lipschitz_std --> (only neeeded for JiT)
- calc_ain ---> calculate Ain Score
- method --> the intended unlearning technique:
- the implemented options are: ('retrain','finetune', 'SCRUM' ,'UNSIR', 'negative_gradiant' , 'lipschitz', 'randomize_label', 'original', 'emmn', 'experimental_method')