

"""simple docstring"""




from typing import List, Optional, TypeVar

from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interleave_iterable_datasets
from .splits import NamedSplit
from .utils import logging
from .utils.py_utils import Literal


A_							:			Dict											= logging.get_logger(__name__)


A_							:			Any											= TypeVar("DatasetType", Dataset, IterableDataset)

def 	A       (     snake_case__		,				snake_case__ = None		,				snake_case__ = None		,				snake_case__ = None		,				snake_case__ = None		,				snake_case__ = "first_exhausted"		,				):




			'''simple docstring'''


			from .arrow_dataset import Dataset
			from .iterable_dataset import IterableDataset

			if not datasets:
						raise ValueError("""Unable to interleave an empty list of datasets."""    )
			for i, dataset in enumerate(snake_case_    ):
						if not isinstance(snake_case_		,				(Dataset, IterableDataset)    ):
									if isinstance(snake_case_		,				(DatasetDict, IterableDatasetDict)    ):
												if not dataset:
															raise ValueError(
															    f"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} """
															    """is an empty dataset dictionary."""    )
												raise ValueError(
												    f"""Dataset at position {i} has at least one split: {list(snake_case_    )}\n"""
												    f"""Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(snake_case_    )    )}\']"""    )
									raise ValueError(
									    f"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(snake_case_    ).__name__}."""    )
						if i == 0:
									SCREAMING_SNAKE_CASE__								=      (
									    (Dataset, IterableDataset) if isinstance(snake_case_		,				snake_case_    ) else (IterableDataset, Dataset)
									)
						elif not isinstance(snake_case_		,				snake_case_    ):
									raise ValueError(
									    f"""Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects."""    )
			if stopping_strategy not in ["first_exhausted", "all_exhausted"]:
						raise ValueError(f"""{stopping_strategy} is not supported. Please enter a valid stopping_strategy."""    )
			if dataset_type is Dataset:
						return _interleave_map_style_datasets(
						    snake_case_		,				snake_case_		,				snake_case_		,				info=snake_case_		,				split=snake_case_		,				stopping_strategy=snake_case_    )
			else:
						return _interleave_iterable_datasets(
						    snake_case_		,				snake_case_		,				snake_case_		,				info=snake_case_		,				split=snake_case_		,				stopping_strategy=snake_case_    )




def 	A       (     snake_case__		,				snake_case__ = None		,				snake_case__ = None		,				snake_case__ = 0		,				):




			'''simple docstring'''


			if not dsets:
						raise ValueError("""Unable to concatenate an empty list of datasets."""    )
			for i, dataset in enumerate(snake_case_    ):
						if not isinstance(snake_case_		,				(Dataset, IterableDataset)    ):
									if isinstance(snake_case_		,				(DatasetDict, IterableDatasetDict)    ):
												if not dataset:
															raise ValueError(
															    f"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} """
															    """is an empty dataset dictionary."""    )
												raise ValueError(
												    f"""Dataset at position {i} has at least one split: {list(snake_case_    )}\n"""
												    f"""Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(snake_case_    )    )}\']"""    )
									raise ValueError(
									    f"""Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(snake_case_    ).__name__}."""    )
						if i == 0:
									SCREAMING_SNAKE_CASE__								=      (
									    (Dataset, IterableDataset) if isinstance(snake_case_		,				snake_case_    ) else (IterableDataset, Dataset)
									)
						elif not isinstance(snake_case_		,				snake_case_    ):
									raise ValueError(
									    f"""Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects."""    )
			if dataset_type is Dataset:
						return _concatenate_map_style_datasets(snake_case_		,				info=snake_case_		,				split=snake_case_		,				axis=snake_case_    )
			else:
						return _concatenate_iterable_datasets(snake_case_		,				info=snake_case_		,				split=snake_case_		,				axis=snake_case_    )





"""simple docstring"""




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


