| from collections import OrderedDict | |
| import torch | |
| def normalize_activation(x, eps=1e-10): | |
| norm_factor = torch.sqrt(torch.sum(x ** 2, dim=1, keepdim=True)) | |
| return x / (norm_factor + eps) | |
| def get_state_dict(net_type: str = 'alex', version: str = '0.1'): | |
| # build url | |
| url = 'https://raw.githubusercontent.com/richzhang/PerceptualSimilarity/' \ | |
| + f'master/lpips/weights/v{version}/{net_type}.pth' | |
| # download | |
| old_state_dict = torch.hub.load_state_dict_from_url( | |
| url, progress=True, | |
| map_location=None if torch.cuda.is_available() else torch.device('cpu') | |
| ) | |
| # rename keys | |
| new_state_dict = OrderedDict() | |
| for key, val in old_state_dict.items(): | |
| new_key = key | |
| new_key = new_key.replace('lin', '') | |
| new_key = new_key.replace('model.', '') | |
| new_state_dict[new_key] = val | |
| return new_state_dict | |