efore inference.

step

<
source
>
(
model_output: FloatTensor
timestep: typing.Union[float, torch.FloatTensor]
sample: FloatTensor
s_churn: float = 0.0
s_tmin: float = 0.0
s_tmax: float = inf
s_noise: float = 1.0
generator: typing.Optional[torch._C.Generator] = None
return_dict: bool = True

)
→
~schedulers.scheduling_utils.EulerDiscreteSchedulerOutput or tuple

Parameters 

model_output (torch.FloatTensor) — direct output from learned diffusi