hedule: str = 'linear'
trained_betas: typing.Union[numpy.ndarray, typing.List[float], NoneType] = None
solver_order: int = 2
prediction_type: str = 'epsilon'
thresholding: bool = False
dynamic_thresholding_ratio: float = 0.995
sample_max_value: float = 1.0
algorithm_type: str = 'dpmsolver++'
solver_type: str = 'midpoint'
lower_order_final: bool = True
**kwargs

)


Parameters 

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