


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      lowerCAmelCase__       (				a):




     '''simple docstring'''


     def __init__(						self ,						__lowerCamelCase ,						__lowerCamelCase = None ,						__lowerCamelCase = None ,						__lowerCamelCase = None ,						__lowerCamelCase = False ,						__lowerCamelCase = False ,						__lowerCamelCase = None ,						**__lowerCamelCase ,						)			->				Any:
            super().__init__(
                __lowerCamelCase ,						split=__lowerCamelCase ,						features=__lowerCamelCase ,						cache_dir=__lowerCamelCase ,						keep_in_memory=__lowerCamelCase ,						streaming=__lowerCamelCase ,						num_proc=__lowerCamelCase ,						**__lowerCamelCase ,						)
            _A      :       Optional[Any]				    = path_or_paths if isinstance(__lowerCamelCase ,						__lowerCamelCase) else {self.split: path_or_paths}
            _A      :       str				    = Text(
                cache_dir=__lowerCamelCase ,						data_files=__lowerCamelCase ,						features=__lowerCamelCase ,						**__lowerCamelCase ,						)


     def  _lowerCamelCase (						self)			->				Any:
            # Build iterable dataset
            if self.streaming:
                   _A      :       int				    = self.builder.as_streaming_dataset(split=self.split)
            # Build regular (map-style) dataset
            else:
                   _A      :       Tuple				    = None
                   _A      :       Tuple				    = None
                   _A      :       Tuple				    = None
                   _A      :       str				    = None

                   self.builder.download_and_prepare(
                       download_config=__lowerCamelCase ,						download_mode=__lowerCamelCase ,						verification_mode=__lowerCamelCase ,						base_path=__lowerCamelCase ,						num_proc=self.num_proc ,						)
                   _A      :       List[str]				    = self.builder.as_dataset(
                       split=self.split ,						verification_mode=__lowerCamelCase ,						in_memory=self.keep_in_memory)
            return dataset





'''simple docstring'''





from transformers import BertTokenizerFast

from .custom_tokenization import CustomTokenizer







class     UpperCAmelCase_       (       _a	):
    """simple docstring"""







    lowercase					=		CustomTokenizer
    pass
