



"""simple docstring"""







from __future__ import annotations

class    UpperCamelCase	:





     """simple docstring"""






     def __init__(       self			:				Tuple						,   _lowerCamelCase			:				str			):
          A__      						= order

          # a_{0} ... a_{k}
          A__      						= [1.0] + [0.0] * order
          # b_{0} ... b_{k}
          A__      						= [1.0] + [0.0] * order

          # x[n-1] ... x[n-k]
          A__      						= [0.0] * self.order
          # y[n-1] ... y[n-k]
          A__      						= [0.0] * self.order





     def     A__	(       self			:				List[str]						,   _lowerCamelCase			:				Optional[Any]						,   _lowerCamelCase			:				Dict			):

          if len(A_			) < self.order:
               A__      						= [1.0, *a_coeffs]

          if len(A_			) != self.order + 1:
               A__      						= (
                   F'''Expected a_coeffs to have {self.order + 1} elements '''
                   F'''for {self.order}-order filter, got {len(A_			)}'''
               )
               raise ValueError(A_			)

          if len(A_			) != self.order + 1:
               A__      						= (
                   F'''Expected b_coeffs to have {self.order + 1} elements '''
                   F'''for {self.order}-order filter, got {len(A_			)}'''
               )
               raise ValueError(A_			)

          A__      						= a_coeffs
          A__      						= b_coeffs





     def     A__	(       self			:				Any						,   _lowerCamelCase			:				Union[str, Any]			):
          A__      						= 0.0

          # Start at index 1 and do index 0 at the end.
          for i in range(1						,   self.order + 1			):
               result += (
                   self.b_coeffs[i] * self.input_history[i - 1]
                   - self.a_coeffs[i] * self.output_history[i - 1]
               )

          A__      						= (result + self.b_coeffs[0] * sample) / self.a_coeffs[0]

          A__      						= self.input_history[:-1]
          A__      						= self.output_history[:-1]

          A__      						= sample
          A__      						= result

          return result










from ..utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_scipy_available,
    is_torch_available,
    is_torchsde_available,
)


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_pt_objects import *  # noqa F403
else:
  from .scheduling_consistency_models import CMStochasticIterativeScheduler
  from .scheduling_ddim import DDIMScheduler
  from .scheduling_ddim_inverse import DDIMInverseScheduler
  from .scheduling_ddim_parallel import DDIMParallelScheduler
  from .scheduling_ddpm import DDPMScheduler
  from .scheduling_ddpm_parallel import DDPMParallelScheduler
  from .scheduling_deis_multistep import DEISMultistepScheduler
  from .scheduling_dpmsolver_multistep import DPMSolverMultistepScheduler
  from .scheduling_dpmsolver_multistep_inverse import DPMSolverMultistepInverseScheduler
  from .scheduling_dpmsolver_singlestep import DPMSolverSinglestepScheduler
  from .scheduling_euler_ancestral_discrete import EulerAncestralDiscreteScheduler
  from .scheduling_euler_discrete import EulerDiscreteScheduler
  from .scheduling_heun_discrete import HeunDiscreteScheduler
  from .scheduling_ipndm import IPNDMScheduler
  from .scheduling_k_dpm_2_ancestral_discrete import KDPMaAncestralDiscreteScheduler
  from .scheduling_k_dpm_2_discrete import KDPMaDiscreteScheduler
  from .scheduling_karras_ve import KarrasVeScheduler
  from .scheduling_pndm import PNDMScheduler
  from .scheduling_repaint import RePaintScheduler
  from .scheduling_sde_ve import ScoreSdeVeScheduler
  from .scheduling_sde_vp import ScoreSdeVpScheduler
  from .scheduling_unclip import UnCLIPScheduler
  from .scheduling_unipc_multistep import UniPCMultistepScheduler
  from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin
  from .scheduling_vq_diffusion import VQDiffusionScheduler

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_flax_objects import *  # noqa F403
else:
  from .scheduling_ddim_flax import FlaxDDIMScheduler
  from .scheduling_ddpm_flax import FlaxDDPMScheduler
  from .scheduling_dpmsolver_multistep_flax import FlaxDPMSolverMultistepScheduler
  from .scheduling_karras_ve_flax import FlaxKarrasVeScheduler
  from .scheduling_lms_discrete_flax import FlaxLMSDiscreteScheduler
  from .scheduling_pndm_flax import FlaxPNDMScheduler
  from .scheduling_sde_ve_flax import FlaxScoreSdeVeScheduler
  from .scheduling_utils_flax import (
      FlaxKarrasDiffusionSchedulers,
      FlaxSchedulerMixin,
      FlaxSchedulerOutput,
      broadcast_to_shape_from_left,
  )


try:
  if not (is_torch_available() and is_scipy_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_torch_and_scipy_objects import *  # noqa F403
else:
  from .scheduling_lms_discrete import LMSDiscreteScheduler

try:
  if not (is_torch_available() and is_torchsde_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ..utils.dummy_torch_and_torchsde_objects import *  # noqa F403
else:
  from .scheduling_dpmsolver_sde import DPMSolverSDEScheduler
