| import torch |
| from torch import Tensor |
|
|
| class BaseScheduler: |
| def alpha(self, t) -> Tensor: |
| ... |
| def sigma(self, t) -> Tensor: |
| ... |
|
|
| def dalpha(self, t) -> Tensor: |
| ... |
| def dsigma(self, t) -> Tensor: |
| ... |
|
|
| def dalpha_over_alpha(self, t) -> Tensor: |
| return self.dalpha(t) / self.alpha(t) |
|
|
| def dsigma_mul_sigma(self, t) -> Tensor: |
| return self.dsigma(t)*self.sigma(t) |
|
|
| def drift_coefficient(self, t): |
| alpha, sigma = self.alpha(t), self.sigma(t) |
| dalpha, dsigma = self.dalpha(t), self.dsigma(t) |
| return dalpha/(alpha + 1e-6) |
|
|
| def diffuse_coefficient(self, t): |
| alpha, sigma = self.alpha(t), self.sigma(t) |
| dalpha, dsigma = self.dalpha(t), self.dsigma(t) |
| return dsigma*sigma - dalpha/(alpha + 1e-6)*sigma**2 |
|
|
| def w(self, t): |
| return self.sigma(t) |
|
|