|
|
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'): |
|
|
|
|
|
url = 'https://raw.githubusercontent.com/richzhang/PerceptualSimilarity/' \ |
|
|
+ f'master/lpips/weights/v{version}/{net_type}.pth' |
|
|
|
|
|
|
|
|
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') |
|
|
) |
|
|
|
|
|
|
|
|
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 |
|
|
|
