




"""simple docstring"""






from typing import Optional

from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader




class   a__			(       UpperCAmelCase__  ):





						def __init__(							self      :	Tuple     ,a__      :	NestedDataStructureLike[PathLike]     ,a__      :	Optional[NamedSplit] = None     ,a__      :	Optional[Features] = None     ,a__      :	str = None     ,a__      :	bool = False     ,a__      :	bool = False     ,a__      :	Optional[int] = None     ,**a__      :	Dict     ,)						->       str:




											"""simple docstring"""







											super().__init__(
											    a__     ,split=a__     ,features=a__     ,cache_dir=a__     ,keep_in_memory=a__     ,streaming=a__     ,num_proc=a__     ,**a__     ,)
											_lowerCAmelCase:Tuple									=  path_or_paths if isinstance(a__     ,a__) else {self.split: path_or_paths}
											_lowerCAmelCase:Optional[Any]									=  Text(
											    cache_dir=a__     ,data_files=a__     ,features=a__     ,**a__     ,)







						def       __UpperCamelCase     (							self      :	Optional[Any])						->       int:




											"""simple docstring"""







											if self.streaming:
																_lowerCAmelCase:Any									=  self.builder.as_streaming_dataset(split=self.split)
											# Build regular (map-style) dataset
											else:
																_lowerCAmelCase:Tuple									=  None
																_lowerCAmelCase:Optional[Any]									=  None
																_lowerCAmelCase:Optional[int]									=  None
																_lowerCAmelCase:Any									=  None

																self.builder.download_and_prepare(
																    download_config=a__     ,download_mode=a__     ,verification_mode=a__     ,base_path=a__     ,num_proc=self.num_proc     ,)
																_lowerCAmelCase:Any									=  self.builder.as_dataset(
																    split=self.split     ,verification_mode=a__     ,in_memory=self.keep_in_memory)
											return dataset












"""simple docstring"""






import warnings

from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor


UpperCamelCase__						=			logging.get_logger(__name__)




class   a__			(       UpperCamelCase_  ):





						def __init__(							self      :	Dict     ,*a__      :	List[str]     ,**a__      :	str)						->       None:




											"""simple docstring"""







											warnings.warn(
											    '''The class PoolFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
											    ''' Please use PoolFormerImageProcessor instead.'''     ,a__     ,)
											super().__init__(*a__     ,**a__)






