


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       (      lowerCamelCase__  ):




      """simple docstring"""







      def __init__(		self      ,							a__      ,							a__ = None      ,							a__ = None      ,							a__ = None      ,							a__ = False      ,							a__ = False      ,							a__ = None      ,							**a__      ,							):



             """simple docstring"""





             super().__init__(
                 a__      ,							split=a__      ,							features=a__      ,							cache_dir=a__      ,							keep_in_memory=a__      ,							streaming=a__      ,							num_proc=a__      ,							**a__      ,							)
             _lowerCamelCase							:     str	=		path_or_paths if isinstance(a__      ,							a__) else {self.split: path_or_paths}
             _lowerCamelCase							:     Tuple	=		Text(
                 cache_dir=a__      ,							data_files=a__      ,							features=a__      ,							**a__      ,							)



      def 				__snake_case			(		self):



             """simple docstring"""





             if self.streaming:
                    _lowerCamelCase							:     Union[str, Any]	=		self.builder.as_streaming_dataset(split=self.split)
             # Build regular (map-style) dataset
             else:
                    _lowerCamelCase							:     List[str]	=		None
                    _lowerCamelCase							:     Optional[int]	=		None
                    _lowerCamelCase							:     Dict	=		None
                    _lowerCamelCase							:     Optional[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							:     Dict	=		self.builder.as_dataset(
                        split=self.split      ,							verification_mode=a__      ,							in_memory=self.keep_in_memory)
             return dataset








import warnings

from .generation import TFGenerationMixin







class 			__A       (      lowerCamelCase__  ):




      """simple docstring"""







      warnings.warn(
          """Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will """
          """be removed in Transformers v5. Import as `from transformers import TFGenerationMixin` instead.""" ,lowerCamelCase__ ,)

