 = 0.02
beta_schedule: str = 'linear'
trained_betas: typing.Union[numpy.ndarray, typing.List[float], NoneType] = None
variance_type: str = 'fixed_small'
clip_sample: bool = True
prediction_type: str = 'epsilon'
**kwargs

)


Parameters 

num_train_timesteps (int) — number of diffusion steps used to train the model.


beta_start (float) — the starting beta value of inference.


beta_end (float) — the final beta value.


beta_schedule (str) —
the