






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










from abc import ABC, abstractmethod
from typing import Optional, Union

from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class     a    ( lowercase__   ):



      """simple docstring"""


      def __init__(      self					:			Any		,      __lowercase					:			Optional[NestedDataStructureLike[PathLike]] = None		,      __lowercase					:			Optional[NamedSplit] = None		,      __lowercase					:			Optional[Features] = None		,      __lowercase					:			str = None		,      __lowercase					:			bool = False		,      __lowercase					:			bool = False		,      __lowercase					:			Optional[int] = None		,      **__lowercase					:			List[str]		,      )							->      Tuple:
        __UpperCAmelCase							:	Any           =  path_or_paths
        __UpperCAmelCase							:	Dict           =  split if split or isinstance(__lowercase		,      __lowercase					) else """train"""
        __UpperCAmelCase							:	Optional[int]           =  features
        __UpperCAmelCase							:	str           =  cache_dir
        __UpperCAmelCase							:	str           =  keep_in_memory
        __UpperCAmelCase							:	Optional[int]           =  streaming
        __UpperCAmelCase							:	Dict           =  num_proc
        __UpperCAmelCase							:	Tuple           =  kwargs




      @abstractmethod
      def 	UpperCAmelCase      (      self					:			List[Any]					)							->      Union[Dataset, DatasetDict, IterableDataset, IterableDatasetDict]:
        pass


class     a    ( lowercase__   ):



      """simple docstring"""


      def __init__(      self					:			List[str]		,      __lowercase					:			Optional[Features] = None		,      __lowercase					:			str = None		,      __lowercase					:			bool = False		,      __lowercase					:			bool = False		,      __lowercase					:			Optional[int] = None		,      **__lowercase					:			Optional[Any]		,      )							->      Optional[int]:
        __UpperCAmelCase							:	Optional[Any]           =  features
        __UpperCAmelCase							:	str           =  cache_dir
        __UpperCAmelCase							:	Optional[int]           =  keep_in_memory
        __UpperCAmelCase							:	Dict           =  streaming
        __UpperCAmelCase							:	Optional[Any]           =  num_proc
        __UpperCAmelCase							:	Union[str, Any]           =  kwargs




      @abstractmethod
      def 	UpperCAmelCase      (      self					:			List[str]					)							->      Union[Dataset, IterableDataset]:
        pass


