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


__lowerCamelCase      :			Tuple							       =		logging.get_logger(__name__)


__lowerCamelCase      :			Optional[Any]							       =		TypeVar('''DatasetType''', Dataset, IterableDataset)



def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	List[DatasetType]			,					__UpperCamelCase   :	Optional[List[float]] = None			,					__UpperCamelCase   :	Optional[int] = None			,					__UpperCamelCase   :	Optional[DatasetInfo] = None			,					__UpperCamelCase   :	Optional[NamedSplit] = None			,					__UpperCamelCase   :	Literal["first_exhausted", "all_exhausted"] = "first_exhausted"			,					)							-> DatasetType:







  """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      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	List[DatasetType]			,					__UpperCamelCase   :	Optional[DatasetInfo] = None			,					__UpperCamelCase   :	Optional[NamedSplit] = None			,					__UpperCamelCase   :	int = 0			,					)							-> DatasetType:







  """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     )







import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


__lowerCamelCase      :			str							       =		logging.get_logger(__name__)







class __snake_case    (						lowerCamelCase_		):




   def __init__(   self      :    List[str]	,     *_lowercase      :    Union[str, Any]	,     **_lowercase      :    Union[str, Any]				):



     """simple docstring"""






     warnings.warn(
         """The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
         """ use DonutImageProcessor instead."""	,     _lowercase	,     )
     super().__init__(*_lowercase	,     **_lowercase				)
