# Reference-Specific Unlearning Metrics Can Hide the Truth: A Reality Check

This codebase is largely based on the UnlearnCanvas benchmark (https://github.com/OPTML-Group/UnlearnCanvas). Please follow the instructions in UnlearnCanvas for setting up the environment, and merge the `diffusion_model_finetuning` folder.

## Instructions
- Finetune the model on full/retain-only datasets: `train_full.sh` and `train_retain.sh`
- Run machine unlearning: follow original instructions from the UnlearnCanvas repo.
- Evaluate using original metrics from UnlearnCanvas: `evaluate_images.sh`
- Generate samples from each model: `sample_compvis_ckpt.sh` and `sample_compvis_unlearned.sh`
- Compute bidirectional likelihoods for FADE computation: `measure_fade.sh`