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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 | |