Keep in mind, torchvision.transforms.Normalize's operations are in-place. If you want immutable implementation,
class NormalizeInverse(torchvision.transforms.Normalize):
"""
Undoes the normalization and returns the reconstructed images in the input domain.
"""
def __init__(self, mean, std):
mean = torch.as_tensor(mean)
std = torch.as_tensor(std)
std_inv = 1 / (std + 1e-7)
mean_inv = -mean * std_inv
super().__init__(mean=mean_inv, std=std_inv)
def __call__(self, tensor):
return super().__call__(tensor.clone())