(self, eta=1.0, s_noise=1.0, *args, **kwargs)
| 160 | |
| 161 | class AncestralSampler(SingleStepDiffusionSampler): |
| 162 | def __init__(self, eta=1.0, s_noise=1.0, *args, **kwargs): |
| 163 | super().__init__(*args, **kwargs) |
| 164 | |
| 165 | self.eta = eta |
| 166 | self.s_noise = s_noise |
| 167 | self.noise_sampler = lambda x: torch.randn_like(x) |
| 168 | |
| 169 | def ancestral_euler_step(self, x, denoised, sigma, sigma_down): |
| 170 | d = to_d(x, sigma, denoised) |