( steps, start, end, bias, amount, exponent, start_offset, end_offset, fad

( sigma: float, sigmas: torch.Tensor, dd_schedule: torch.Tensor, )

(schedule)

(cls)

(cls)

(s)

(cls)

(steps)

( model: object, x: torch.Tensor, sigmas: torch.Tensor, *, dds_wrapped_sampler: object,

( cls, sampler: object, *, detail_amount, start, end,

(cls, sampler, dishonesty_factor, *, start_percent=0.0, end_percent=1.0)

( model, x, sigmas, *, lss_wrapped_sampler, lss_dishonesty_factor, lss_startend_pe

( self, sigmas, detail_amount, start, end, bias, expon

(x: torch.Tensor, sigma: torch.Tensor, **extra_args: dict)

(self, sigmas, factor, start, end)