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from abc import ABC, abstractmethod
import torch
class DiffusionLossWeighting(ABC):
@abstractmethod
def __call__(self, sigma: torch.Tensor) -> torch.Tensor:
pass
class UnitWeighting(DiffusionLossWeighting):
def __call__(self, sigma: torch.Tensor) -> torch.Tensor:
return torch.ones_like(sigma, device=sigma.device)
class EDMWeighting(DiffusionLossWeighting):
def __init__(self, sigma_data: float = 0.5):
self.sigma_data = sigma_data
def __call__(self, sigma: torch.Tensor) -> torch.Tensor:
return (sigma**2 + self.sigma_data**2) / (sigma * self.sigma_data) ** 2
class VWeighting(EDMWeighting):
def __init__(self):
super().__init__(sigma_data=1.0)
class EpsWeighting(DiffusionLossWeighting):
def __call__(self, sigma: torch.Tensor) -> torch.Tensor:
return sigma**-2.0
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