Constructs an exponential noise schedule.
(n, sigma_min, sigma_max, device='cpu')
| 24 | |
| 25 | |
| 26 | def get_sigmas_exponential(n, sigma_min, sigma_max, device='cpu'): |
| 27 | """Constructs an exponential noise schedule.""" |
| 28 | sigmas = torch.linspace(math.log(sigma_max), math.log(sigma_min), n, device=device).exp() |
| 29 | return append_zero(sigmas) |
| 30 | |
| 31 | |
| 32 | def get_sigmas_polyexponential(n, sigma_min, sigma_max, rho=1., device='cpu'): |
nothing calls this directly
no test coverage detected