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import torch | |
from .modules.lpips import LPIPS | |
def lpips(x: torch.Tensor, | |
y: torch.Tensor, | |
net_type: str = 'alex', | |
version: str = '0.1'): | |
r"""Function that measures | |
Learned Perceptual Image Patch Similarity (LPIPS). | |
Arguments: | |
x, y (torch.Tensor): the input tensors to compare. | |
net_type (str): the network type to compare the features: | |
'alex' | 'squeeze' | 'vgg'. Default: 'alex'. | |
version (str): the version of LPIPS. Default: 0.1. | |
""" | |
device = x.device | |
criterion = LPIPS(net_type, version).to(device) | |
return criterion(x, y) | |