vishal3477 / Reverse_Engineering_GMs

Official Pytorch implementation of paper "Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images"
132 stars 18 forks source link

The .npy files in the rev_eng_updated.py could not be found in the main folders or the .zip or tar.gz file #15

Closed zhangtzq closed 1 year ago

zhangtzq commented 1 year ago

The .npy files in the rev_eng_updated.py could not be found in the main folders or the .zip or tar.gz file. The lost .npy files are in the following codes:

ground_truth_net_all=torch.from_numpy(np.load("ground_truth_net_131_15dim.npy")) ground_truth_loss_9_all=torch.from_numpy(np.load("ground_truth_loss_131_10dim.npy"))

ground_truth_net_all_dev=torch.from_numpy(np.load("net_dev_131_dim.npy")) ground_truth_loss_9_all_dev=torch.from_numpy(np.load("ground_truth_loss_131_10dim.npy"))

ground_truth_net_cluster=torch.from_numpy(np.load("net_cluster_131_dim.npy")) ground_truth_loss_9_cluster=torch.from_numpy(np.load("loss_cluster_131_dim.npy"))

ground_truth_net_all=torch.from_numpy(np.load("random_ground_truth_net_arch_91_15dim.npy"))

ground_truth_loss_all=torch.from_numpy(np.load("random_ground_truth_loss_91_3dim.npy"))

ground_truth_loss_9_all=torch.from_numpy(np.load("random_ground_truth_loss_91_9dim.npy"))

ground_truth_p=torch.from_numpy(np.load("p131.npy"))

If you could tell me where I can find them, thank you very much. Best wishes!

zhangtzq commented 1 year ago

I am sorry to bother you. Besides the above issues, I also can not find the classificition_39/34/37 model which are defined in the the rev_eng_updated.py.

vishal3477 commented 1 year ago

Hi @zhangtzq , I'm really sorry for the inconvenience caused. The files are uploaded in the latest release. Please check it out and let me know if you face any difficulties.

zhangtzq commented 1 year ago

Thank you, and I find the updated files.